2012 Themed Meeting: Developmental Methodology

February 9 – February 11, 2012

Tampa Marriott Waterside Hotel & Marina Tampa, Florida Table of Contents

Program Co-Chairs’ Welcome ...... 2

Meeting Information ...... 3

Review Panels ...... 4

Meeting Session Listing ...... 5

Thursday ...... 5

Invited Workshops ...... 5-7

Invited Talk ...... 9

Plenary Session ...... 11

Welcome Reception ...... 12

Friday ...... 12

Invited Workshops ...... 12-14

Invited Talk ...... 15

Plenary Session ...... 18

Poster Session with Refreshments ...... 19

Ask-A-Question Poster Session with Refreshments...... 27

Saturday ...... 27

Invited Workshops ...... 27-30

Author Index ...... 32

Meeting Level Floor Plan ...... 40

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Program Co-Chairs’ Welcome

Welcome to Tampa and the Developmental Methodology themed meeting of the Society for Research in Child Development. As you glance at the program you see that this unique meeting provides exciting opportunities for learning, discussing, and networking with developmental methodologists from around the world.

The term “developmental methodology” describes an area of research and scholarship that has existed rather informally until this meeting. We view developmental methodology as the interface of developmental science and quantitative methodology. These two fields of inquiry have ebbed and flowed in a scholarly dance for some time. The advances in methodology improve the study of child development, while the unique research questions of child development motivate advancements in quantitative methods. The field of developmental methodology, therefore, is more than the addition of developmental designs and quantitative analyses; it is a synergistic combination that offers unique opportunities and challenges emergent only at the interface of these disciplines. Todd D. Little Noel A. Card This conference is our attempt to provide a forum and a modern identity to what has been an informal network of innovators and collaborators across the quantitative and developmental sciences areas of inquiry.

In attempting to organize this emergent area, we arranged the program around several themes (listed on page 4), intended to capture many of the design, measurement, and data analysis considerations in developmental science. Across these themes, numerous formats for presentation and discussion are utilized. Several workshops provide more extensive descriptions of topics, intended to help attendees learn methodological tools. More traditional formats of invited talks, paper symposia, and poster symposia present states of the art in developmental methodology. We also added a new “Ask a Question” format that allows presenters the chance to discuss with attendees challenging methodological issues in developmental science. Finally, we are especially excited by two keynote addresses by Peg Burchinal and John Nesselroade, both innovators in developmental methodology even before the phrase existed.

Over two years of planning went into this conference, and we have accumulated a considerable debt to many individuals for their hard work and thoughtful input. First and foremost, we want to thank the SRCD staff for organizing the logistics of this meeting. We also want to thank Greg Duncan, Lonnie Sherrod, and Susan Lennon for their many insights during the initial planning of this meeting. More generally, we want to thank SRCD for holding this meeting, which we view as the Society’s commitment to advancing the rigor of our science. We also owe our thanks to the invited speakers of this conference, the panel chairs, and the expert reviewers of the submitted program. Finally, we want to thank you, in advance, for what we anticipate will be exciting and thought-provoking discussion throughout the meeting.

Thank you for attending the 2012 Developmental Methodology meeting. If you have any questions or suggestions, or simply want to introduce yourself, please do not hesitate to talk with either of us or with the SRCD staff.

Sincerely,

&

Noel A. Card and Todd D. Little Program Co-Chairs

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Developmental Methodology 2012 Meeting Information

All events and sessions will be held in:

Tampa Marriott Waterside Hotel & Marina 700 South Florida Avenue Tampa, FL 33602

Always Wear Your BADGE – it identifies your registration and restricts you to the meeting for which you registered! Badges should be worn at all times, not only as a courtesy to other attendees, but also as an indication that you have registered before participating in any scheduled event. Badges must be worn to gain admission to the meeting sessions, poster session, and reception for the Developmental Methodology meeting. If you lose or forget your badge you may have it reprinted at the registration desk (located to the left of the top of the escalator on the 2nd floor of the hotel). Thank you for your cooperation!

Registration Desk The registration desk is located to the left of the top of the escalator on the 2nd floor of the hotel.

Registration Desk hours:

Wednesday 4:00 PM – 7:00 PM Thursday 6:30 AM – 4:00 PM Friday 7:00 AM – 4:15 PM Saturday 7:00 AM – 11:30 AM

Speaker-Ready Room The speaker-ready room is located in Meeting Room 11 on the 3rd floor of the hotel. This room is equipped with a screen, LCD projector, a table, and chairs.

Speaker-Ready Room hours:

Thursday 6:30 AM – 4:00 PM Friday 7:00 AM – 4:15 PM Saturday 7:00 AM – 10:15 AM

Special Events: Coffee and a light breakfast will be available in the Grand Salon EF Foyer:

Thursday 7:30 AM – 8:00 AM Friday 7:30 AM – 8:00 AM Saturday 7:30 AM – 8:00 AM

Welcome Reception in the Grand Salon EF Foyer from 4:30 PM – 6:00 PM. All attendees are encouraged to come! Please join us for wonderful hors d’oeuvres and an open bar.

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2012 Review Panels for Developmental Methodology

A sincere thank you to all those involved in the review process! Your time and efforts are very much appreciated.

Theme 1: Scaling Chaired by: Larry R. Price Reviewers: Danielle Brown with mentees Chastity McFarlan and Marcia Calloway, Rachel Gordon with mentee Ken A. Fujimoto, Yibing Li, Amanda Pearl, Gary Resnick, Gail Ryser, Manfred van Dulmen, Naomi Wentworth, Nikki Yonts.

Theme 2: Measurement equivalence Chaired by: Daniel J. Bauer and Patrick Curran Reviewers: Annamaria Csizmadia, Natalie Eggum, Margaret K. Keiley, Peggy S. Keller, Michelle Lampl, Christine Merrilees with mentee Laura Taylor, Thomas M. Olino, Stephanie D. Stepp, Melissa Sturge-Apple, Deanne Swan.

Theme 3: Intensive data collection methods Chaired by: Scott Hofer Reviewers: Jeremy Biesanz, Niall Bolger, Daniel Bontempo, Jacqueline Mogle, Graciela Muniz, Brian Ogolsky, Andrea Piccinin, Annie Robitaille, Joshua Smyth, Catharine Sparks, Robert Stawski, Valgeir Thorvaldsson.

Theme 4: Content-specific measurement Chaired by: Antonio Morgan-Lopez Reviewers: Beth A. Bailey, Carla Bann, Kortnee Barnett-Walker, Joann P. Benigno, Ximena Franco, Eun Sook Kim, Assaf Oshri, Lissette Saavedra.

Theme 5: Innovative longitudinal designs Chaired by: Antonius H. Cillessen Reviewers: Amy D. Bellmore, William J. Burk, James A. Dixon, Patrick S. Malone, Karen Nylund- Gibson, Holly Schindler, Sara Tomek Templin, Rens van de Schoot.

Theme 6: Intraindividual longitudinal analysis Chaired by: Nilam Ram Reviewers: Annette Brose, Marcia Calloway, Sy-Miin Chow, Kristine Marceau, Ashley Mason, Chastity McFarlan, Matthias Mehl, Jennifer Morack, Florian Schmiedek, Mariya Shiyko, Lijuan (Peggy) Wang, Li Weilin, Phil Wood.

Theme 7: Interindividual longitudinal analysis Chaired by: James P. Selig Reviewers: Yvonne Anders, Naomi Ekas, John Geldhof, Sharon R. Ghazarian, Allen Gottfried with mentee Erin Arruda, Suzanne Hartman, Paul E. Jose, Christopher Lloyd, Florensia F. Surjadi, Yan Z. Wang.

Theme 8: Combining intraindividual and interindividual longitudinal analysis Chaired by: Kevin J. Grimm Reviewers: Stephen Aichele, Nayena Blankson with mentee Shana Rochester, Wes Bonifay, Jan Boom, Laura Castro-Schilo, Kai Cortiina, Ryne Estabrook, Melissa R.W. George, Christopher A. Hafen, Jon Helm, Scott Monroe, Joel Steele.

Theme 11: Missing data Chaired by: Mijke Rhemtulla Reviewers: Chantelle Dowsett, Carl Falk, Kim Gibson, Ross Larsen, Weilin Li, Gabriel Schlomer, Elliot Tucker-Drob, Amanda Williford with mentee Michelle Maier.

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Thursday, 7:30 am - 8:00 am be discussed throughout the workshop. By the end of the course, participants should possess a (Event 1-001) Coffee familiarity with the analytic approach of general Grand Salon EF Foyer growth mixture modeling, such that they may Thursday, 7:30 am – 8:00 am competently evaluate the quality of applications of GGMM in the developmental literature, and a solid foundation to pursue additional training in 1-001. Coffee and Continental Breakfast order to develop their facilities for successfully applying GGMM in their own work. Thursday, 8:00 am - 11:45 am Biography. Dr. Katherine (Event 1-002) Invited Workshop Masyn, currently an Grand Salon A Assistant Professor at the Thursday, 8:00 am - 11:45 am Harvard Graduate School of Education, received her 1-002. Growth Mixture Modeling and doctorate in Social Beyond: Longitudinal Analysis with Research Methodology at Continuous and Categorical Latent UCLA under the mentorship Variables of Prof. Bengt Muthén. She Instructors: Katherine E. Masyn, Hanno Petras completed her postdoctoral training in Prevention Abstract. This short course is designed for Science Methodology researchers with a working knowledge of growth through a NIMH-funded fellowship held by Johns modeling in either a multilevel or SEM Hopkins University and worked as an Assistant framework. The goal of the workshop is to Professor in Human Development at UC Davis introduce participants to latent growth curve before moving in January 2010 to her present modeling with a combination of continuous and position. Dr. Masyn's research focuses on the categorical latent variables, including latent class development and application of latent variable growth analysis (also known as semi-parametric statistical models related to: survival and event group-based trajectory models) and the more history analysis; multivariate and multi-faceted flexible general growth mixture modeling. The longitudinal processes, e.g., latent transition course will begin with an introduction to growth mixture models; and, more broadly, the unconditional growth mixture models involving characterization and parameterization of both discussions of model specification, estimation, observed and unobserved population and interpretation. Appropriate emphasis will be heterogeneity in cross-sectional and longitudinal given to one of the more challenging aspects of settings, e.g., factor mixture models. Along with any mixture modeling: class enumeration. We will her own methods research, Dr. Masyn also enjoys then move on to general growth mixture models close collaborations with colleagues from the (GGMMs), examining methods for the inclusion of fields of Human Development, Education, both antecedents (predictors and correlates) and Psychology, Public Health, and Prevention consequences (“distal outcomes”) of trajectory Science and serves as the statistical consultant on class membership. The workshop will conclude multiple federally-funded research grants. with an overview of some of the many extensions of GGMM possible in the broader latent variable Biography. Dr. Hanno modeling framework, including latent transition Petras, currently the growth mixture models, multilevel growth Associate Director of the mixture models, and joint survival and growth Center for Health and Social models. During the course, we will stress Policy Research at JBS principled model building strategies, International, Inc., received demonstrated with real data examples. Strengths his doctorate in Sociology and limitations of the methods, as well as the from Christian-Albrechts common misapplications and misinterpretations University in Kiel, Germany that have resulted in some of the standing and completed his criticisms of GGMM in the extant literature, will postdoctoral training in

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Prevention Science funded by a NIMH fellowship workshop is designed to provide those attending at Johns Hopkins University. His research with an overview of the fundamentals of ML-SEM. interests and expertise are in the development of It is intended for those who have some familiarity antisocial behavior, the design and evaluation of with both SEM and MLM. We will begin with a preventive interventions and the appropriate brief review of the foundations of MLM and SEM application of statistical methods using latent and then introduce a unified model for ML-SEM variables. Dr. Petras is an experienced reviewer with special attention to how it differs from the for peer reviewed journals and an active SEM and MLM specifications. Topics covered will participant on advisory panels. In addition, he is include: Multilevel Confirmatory Factor Analysis; a member of the Prevention Science Methodology Multilevel Path Analysis; and issues of model fit in Workgroup. Finally, he is the current editor for ML-SEM. Examples using the Mplus software SPR Community, the newsletter of the Society for package will be provided for both longitudinal Prevention Research (SPR), a consulting editor for and cross-sectional data. Prevention Science and also serves on the Board of Directors of SPR. He is well-published in the Biography. James P. Selig, areas of violence, substance use, and mental Ph.D., is an assistant health and has applied latent variable models in professor of educational the majority of his papers. Drs. Masyn and Petras psychology at the University share a strong commitment to the effective and of New Mexico. He holds a accessible dissemination of emerging statistical Ph.D. in quantitative methodology to substantive researchers and have psychology from the taught, both individually and as a team, University of Kansas. His numerous trainings and workshops, both areas of interest include nationally and internationally, on the topics of: models for longitudinal data, latent variable growth modeling and growth multilevel modeling, and mixture modeling; latent class and latent structural equation modeling. transition analysis; multilevel modeling; and discrete- and continuous-time survival analysis. (Event 1-004) Invited Workshop Grand Salon C (Event 1-003) Invited Workshop Thursday, 8:00 am - 11:45 am Grand Salon B Thursday, 8:00 am - 11:45 am 1-004. Making Missing Data Work: Theory and Application of Planned Missing Designs 1-003. Introduction to Multilevel Structural for Developmental Research Equation Modeling Instructors: Wei Wu, Mijke Rhemtulla Instructor: James P. Selig Abstract. The goal of this workshop is to make Abstract. Multilevel Structural Equation Modeling participants well-versed in planned missing data (ML-SEM) is a relatively new approach that designs, from conceptualization to the details of incorporates some of the best features of two design and carry-out, to analysis. To reach this distinct modeling traditions: Multilevel Modeling goal, the workshop will begin with a brief but (MLM) and Structural Equation Modeling (SEM). thorough introduction to the problem of missing This approach is exciting because it can be used data and modern missing data mechanisms. We to accommodate nested data structures (e.g., will then discuss in detail several specific repeated observations within individuals or planned-missing designs. Finally, we will explain students within classrooms) while also how to compute power for designs with missing incorporating a measurement model to correct data. (1) Characteristics of Missing Data. It is for measurement error, and allowing the important to be able to characterize missing specification of complex relations among many data, whether it stems from a planned missing latent and observed variables. The idea of ML- design or other reasons (e.g., attrition, SEM is not new, but innovations occurring over nonresponse, computer failure). Too few the past several years in ML-SEM software have published papers even mention missing data, with made it possible to estimate a wide variety of the result that important biases in their results models that were previously unavailable. This may go unnoticed. Participants will first learn the

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conceptual differences between missing data Biography. Dr. Wei Wu is mechanisms (Missing Completely at Random, an assistant professor of Missing at Random, Missing Not at Random), and Quantitative Psychology learn how to tell which of these mechanisms is and research affiliate in most likely to apply to their particular dataset the Center of Research (e.g., by inspecting missing data patterns and Method and Data Analysis percentages, and by regressing missingness at the University of indicators on other variables in the dataset). Kansas. She completed her These steps can be accomplished using any Ph.D. in Quantitative statistical software, such as SPSS. (2) Modern Psychology from Arizona Missing Data Methods. The next part of the State University in 2008. workshop will feature a brief overview of Multiple Wu is a specialist in Imputation and Full Information Maximum structural equation modeling, longitudinal data Likelihood, the two modern missing data methods analysis and missing data estimation. She that should be used in almost any analysis where currently serves as co-PI on a research grant missing data are involved. Software options for funded by NSF developing and evaluating planned the two methods will be presented. Participants missing data designs in longitudinal studies. She will learn how to perform “Rubin’s Rules” for regularly teaches multiple regression, combining estimates across multiple imputations; multivariate statistics, advanced SEM and missing they will also learn how to use the variance data analysis. components in Rubin’s Rules (i.e., within- and between-imputation variances) to compute Biography. Mijke fractions of missing information for parameters of Rhemtulla, Ph.D., is a interest. (3) Planned Missing Designs. With postdoctoral researcher fundamentals covered, participants will learn at the Center for about three types of planned missing designs. The Research Methods and Multi-Form Design (Graham, Hofer, & Piccinin, Data Analysis at the 1994) takes a long test or survey and makes it University of Kansas. significantly shorter for each participant, Mijke received her PhD alleviating participant fatigue and drop-out, but from the University of retaining a large number of items. The Wave- British Columbia in 2010 Missing Design (Graham, Taylor, & Cumsille, in Developmental 2001) is for longitudinal designs; here, Psychology. Her participants are measured at some but not all quantitative research focuses on understanding waves of measurement. Finally, the Two-Method how standard errors are affected by missing data Design (Graham, Taylor, Olchowski, & Cumsille, (i.e., fraction of missing information). 2006) is used when it is possible to measure a construct with an unbiased time- or cost- Thursday, 8:00 am - 9:45 am intensive method (e.g., personal interviews) or a biased but inexpensive method (e.g., paper-and- (Event 1-005) Paper Symposium pencil tests). By administering the intensive Grand Salon D measure to a small proportion of the total sample Thursday, 8:00 am - 9:45 am and administering the inexpensive method to the entire sample, it is possible to measure and 1-005. Modeling Individual & Dyadic remove the bias, maximizing validity as well as Processes: New Time Series Methods cost-efficiency. Participants will learn which (if Chairs: Peter Molenaar, Nilam Ram any) design is appropriate for their research Pennsylvania State University question and measures, how to implement these designs, and how to minimize power loss for  Dynamic Models for Dyadic Interactions in important parameters. (4) Power Analyses. If Developmental Research there is time remaining, participants will learn Emilio Ferrer1, Joel Steele2 1 2 how to use a Monte Carlo simulation approach to University of California; Portland State measure power of a design with a specified University amount of missing data, using Mplus.

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 A Novel Method for Obtaining Functional MRI Thursday, 10:00 am - 11:45 am Connectivity Maps Kathleen Gates, Peter Molenaar (Event 1-007) Constructed Paper Symposium Pennsylvania State University Grand Salon D Thursday, 10:00 am - 11:45 am  Time-Frequency Analysis for Modeling 1-007. Assessing Measurement Across Physiological Dynamics in Dyadic Interactions Time, Development, and Contexts Siwei Liu1, Peter Molenaar1, Michael Rovine1, Matthew Goodwin2 Chair: M. Lee Van Horn 1Pennsylvania State University; University of South Carolina 2Massachusetts Institute of Technology Media  Cross-National Equivalency of Communities Laboratory That Care-based Risk and Protective Factor Scales Between the United States and  Day-to-Day Person-Specific Processes of Australia Social Anxiety in Vulnerable University Eric Brown1, Jennifer Beyers4, Richard Freshman Catalano1, Todd Herrenkohl1, John Cynthia Campbell, Karen Bierman, Peter Toumbourou2, M. Lee Van Horn3 Molenaar 1University of Washington; 2Deakin University; Pennsylvania State University 3University of South Carolina; 4Organizational Research Services

(Event 1-006) Paper Symposium  Factorial Invariance of an early measure of Meeting Room 12 mathematics: Evaluating stability through Thursday, 8:00 am - 9:45 am kindergarten across three research groups 1 2 1-006. Advances in longitudinal modeling Christopher Wolfe , Douglas Clements , Julie 2 2 applied to literacy research Sarama , Mary Elaine Spitler 1Indiana University - Kokomo; 2University at Chair: Yaacov Petscher Buffalo Florida Center for Reading Research  Methodological and Statistical Considerations  Testing Longitudinal Invariance of a Dynamic in Detecting Matthew Effects Developmental Construct: Executive Control Christopher Schatschneider2, Yaacov Across the Preschool Years 1 2 Petscher1 Kimberly Andrews Espy , Tiffany Sheffield , 2 2 1Florida Center for Reading Research; 2Florida Hye-Jeong Choi , Jennifer Nelson , Caron 2 State University Clark 1 1. Office for Research, Innovation and Graduate Education, University of Oregon;  Modeling within-person change using latent 2University of Nebraska-Lincoln change models Donald Compton Vanderbilt University  A Comparison of Estimators for Latent Growth Models with Partially Invariant Ordinal Repeated Measures  A multilevel bifactor framework for the Hye-Jeong Choi measurement of instruction University of Nebraska-Lincoln Ben Kelcey

Wayne State University

 Linear and non-linear models for growth and change: examples from the National Longitudinal Study of Youth Ann O'Connell1, Jessica Logan1, Jill Pentimonti1, Betsy McCoach2 1 2 Ohio State University; University of Connecticut

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(Event 1-008) Invited Talk change score analysis of a randomized clinical Meeting Room 12 trial in reasoning training. Psychology and Aging, Thursday, 10:00 am - 11:45 am 23(4), 702-719. PMCID: 19140642

1-008. Slowly Moving from Repeated Biography. John J. (Jack) Measures ANOVA to Dynamic BUT McArdle, Ph.D., is Senior Structural Modeling Professor of Psychology at Chair: Noel A. Card the University of Southern University of Arizona California where he heads Invited Speaker: John J. (Jack) McArdle the Quantitative Methods training program and is Abstract. The predominance of Repeated Chair of the research Measures ANOVA (RANOVA) in longitudinal data Committee. He teaches analysis is considered. RANOVA is a readily classes in topics in available, and widely respected way to test mean psychometrics, multivariate changes over time, so it is a widely used analysis, longitudinal data technique in both observational and manipulation analysis, exploratory data mining, and structural research. Controversies about the required equation modeling. His research has been focused covariance assumptions of the data (i.e., on age-sensitive methods for psychological and compound symmetry) have been largely settled educational measurement and longitudinal data by the use of an epsilon factor to correct the analysis including publications in factor analysis, probability values. There is no doubt that growth curve analysis, and dynamic modeling of RANOVA is a special and useful technique. But adult cognitive abilities. Jack was recently the recent surge of activity in Longitudinal awarded an NIH-MERIT grant from the National Structural Equation Models (LSEM) should not be Institute on Aging for his work on “Longitudinal ignored either. Although it is not often stated, and Adaptive Testing of Adult Cognition.” (2005- the RANOVA can be thought of and fitted as a 2015), and here he is working on new adaptive special case of the more general LSEM approach. tests procedures to measure higher order That is, exactly the same parameter values and cognition as a part of standard surveys (e.g. the fit indices can be obtained from RANOVA or SEM HRS). Working with the American Psychological programs. As soon as this basic RANOVA option is Association he has led the Advanced Training demonstrated in LSEM, other longitudinal Institute’s on both Longitudinal Structural modeling approaches become clear - including Equation Modeling (2000-2011) and Exploratory the recent surge of activity in latent growth Data Mining (2009-2011). curve modeling and latent change score analysis. The need for these new approaches to dynamic Thursday, 1:30 pm - 3:15 pm analysis comes largely when we want to examine hypotheses about the individual differences in (Event 1-009) Paper Symposium changes. This focus on the individual and their Grand Salon A changes is not a formal property of RANOVA. The Thursday, 1:30 pm - 3:15 pm LSEM is not considered the final statement here, and Exact Differential Models or Chaos Models 1-009. Applications of Recent Advances in can be used instead. To clarify this first option, Causal Inference Methodology to numerical examples are presented using standard Longitudinal Data SEM and SAS software. The key dynamic question Chairs: Christopher Powers, Donna Coffman arises - “What is your model for change?” The Pennsylvania State University biggest surprise comes when many researchers have questions and ideas that are well beyond  Investigating the Causal Relationship Between the RANOVA approaches they use, and the LSEM Parental Knowledge and Youth Risky Behavior approaches would be much more suitable for Melissa Lippold, Donna Coffman, Mark evaluating their own ideas. McArdle, J.J. (2008). Greenberg Latent variable modeling of differences and Pennsylvania State University changes with longitudinal data. Annual Review of Psychology, 60, 577-605. PMCID: 18817479 McArdle, J.J. & Prindle, J.J. (2008). A latent

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 Novel Approaches to Causal Mediation in the (Event 1-011) Paper Symposium Context of Clinical Trials Grand Salon C Scott Compton2, Donna Coffman1 Thursday, 1:30 pm - 3:15 pm 1Pennsylvania State University; 2Duke 1-011. Using Regression Mixtures to Model University Medical Center Individual Differences  Causal Mediation of Inattention and Chair: M. Lee Van Horn1 Aggression on Substance Use Outcomes in the Discussant: Hanno Petras2 Fast Track Data 1University of South Carolina; 2JBS International, Donna Coffman, Christopher Powers, Karen Inc. Bierman  Moderation without a Moderator: Using Pennsylvania State University Regression Mixtures to Find Differential

Effects of Contexts M. Lee Van Horn1, Thomas Jaki2 (Event 1-010) Constructed Paper Symposium 1University of South Carolina; 2Lancaster Grand Salon B University Thursday, 1:30 pm - 3:15 pm 1-010. Issues in and Applications of Latent  A Novel Approach for Dealing with Non- Trait and Class Analysis in Longitudinal Normal Errors When Using Regression Mixture Research Models Melissa George1, Na Yang2, M. Lee Van Horn1 Chair: Larry R. Price 1University of South Carolina; 2AdvanceMed Mind Spring Corporation  Using a Latent Trait-State-Occasion Model to Study the Relationships Between  Identifying Heterogeneity with Multilevel Developmental Phenotypes of Internalizing Regression Models and Multilevel Regression Symptoms and Single Nucleotide Mixture Models Polymorphisms Tan Li, Melissa George Rashelle Musci1, Katherine Masyn2, Nicholas University of South Carolina Ialongo3, George Uhl4 1University of California-Davis; 2Harvard University; 3Bloomberg School of Public (Event 1-012) Paper Symposium Health, Johns Hopkins University; 4Johns Grand Salon D Hopkins University Thursday, 1:30 pm - 3:15 pm

 Blatant Class Analysis 1-012. Measurement Issues in the Study of Eric Loken Change Pennsylvania State University Chair: Kevin J. Grimm  Predicting longitudinal outcomes using the University of California, Davis latent transition analysis model: Early prediction of degree attainment  Factorial Invariance in Longitudinal Karen Nylund-Gibson1, Amber Gonzalez1, Investigations: Accurately Charting Growth Gottfried Allen2, Adele Gottfried3 Over Time 1University of California, Santa Barbara; Keith Widaman, Kevin Grimm 2Claremont Graduate University; 3California University of California, Davis State University, Northridge  Testing the Number of Factors and Factorial  Prediction in Growth Mixture Models: New Invariance with Longitudinal Data Approaches From Data Mining to Predict Ryne Estabrook Parameters, Classes, and Distal Outcomes 1 1 2 Virginia Commonwealth University Richard Gonzalez , WonJung Oh , Tianyi Yu , Brenda Volling1 1 2 University of Michigan; University of Georgia

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 Using Measurement at Multiple Time-Scales to Thursday, 3:15 pm - 3:30 pm Articulate Developmental Theory Nilam Ram, David Conroy, Aaron Pincus, (Event 1-014) Afternoon Break Denis Gerstorf, Peter Molenaar Grand Salon EF Foyer Pennsylvania State University 3:15 pm – 3:30 pm

 Measurement Model Effects on Studying 1-014 Afternoon Refreshments Change Kevin Grimm1, Anthony Kuhl1, Zhiyong Zhang2 1 2 Thursday, 3:30 pm - 4:30 pm University of California, Davis; Notre Dame University (Event 1-015) Plenary Session Grand Salons E-F Thursday, 3:30 pm - 4:30 pm (Event 1-013) Paper Symposium Meeting Room 12 1-015. Some Methodological Matters I Wish Thursday, 1:30 pm - 3:15 pm I Had Thought About Sooner 1-013. Contemporary Behavior Genetic Co-Chairs: Noel A. Card, Todd D. Little Methods Elucidate Developmental Process Keynote Speaker: John R. Nesselroade Chairs: Soo Rhee1, Kathryn Lemery-Chalfant2 Abstract. Calls for behavioral researchers to 1University of Colorado at Boulder; 2Arizona State recognize and better take into account that the University individual should be the primary unit of analysis have recurred over many decades. This call is as  Combining Behavioral Genetic and salient for developmentalists as for members of Longitudinal Approaches to Testing any other sub-discipline. Some of the dangers of Hypotheses about Specific Environmental not doing so were recently made evident by Influences on Development Molenaar (2004) in his discussion of ergodicity K. Paige Harden, Patrick Quinn, Elliot and his advancement of the argument that most Tucker-Drob developmental processes are not ergodic. In this University of Texas at Austin talk, I focus on several key areas of research that have been pursued mainly from a between-  Intergenerational Transmission of Genetic persons, individual differences orientation (e.g., Risk for Psychopathology: Employing a Latent measurement models, prediction and selection, Variable Approach to Risk Estimation generalizability) and consider how the attendant Gordon Harold1, Kimberly Rhoades2, Jenae research methodology might be re-structured in a Neiderhiser3, Misaki Natsuaki4, Daniel Shaw5, more individually-oriented direction. I will David Reiss6, Leslie Leve2 discuss some current work but also point to what 1University of Leicester; 2Oregon Social I believe may turn into some future work by the Learning Center; 3The Pennsylvania State generations of researchers succeeding mine. In 4 University; The University of California, the process, I shall hope to "take a few bites of Riverside; 5The University of Pittsburgh; 6Yale hands that have fed me" along the way -- not to Child Study Center cripple and maim so much as to secure attention.

 Behavior Genetic Modeling of Gene- Biography. John R. Environment Interplay: Using GxE and rGE to Nesselroade earned his BS Understand Mechanisms of Development degree in Mathematics Susan South (Marietta College, 1961) Purdue University and MA and PhD degrees in Psychology (University of Illinois at Urbana- Champaign, 1965, 1967). Prior to moving to UVA in 1991, Nesselroade spent five years at West Virginia University and 19

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years at The Pennsylvania State University. He and then to provide guidance for current has been a frequent visiting scientist at the Max practices in computing these analyses. These Planck Institute for Human Development, Berlin. analytic techniques are not well taught in current Nesselroade is a past-President of APA's Division textbooks, and widespread ignorance and 20 (1982-83) and of the Society of Multivariate misconceptions prevail. The Baron and Kenny Experimental Psychology (1999-2000). He is a approach will be taught, but its extension into Fellow of the American Association for the higher order platforms such as structural Advancement of Science, the American equation modelling (SEM), multi-level modelling, Psychological Association, the Association for and bootstrapping will also be made. A working Psychological Science, and the Gerontological knowledge of multiple regression will be Society of America. Other honors include the R. assumed, but familiarity with higher order B. Cattell Award and the S. B. Sells Award for statistical methods (e.g., SEM, multilevel Distinguished Lifetime Achievement from the modeling) is not necessary, but will be helpful. Society of Multivariate Experimental Psychology The first portion of the workshop will be devoted and the Gerontological Society of America’s to statistical mediation and the second portion to Robert F. Kleemeier Award. In 2010, Nesselroade statistical moderation. received an honorary doctorate from Berlin’s Humboldt University. He is currently working on Biography. Associate the further integration of individual level Professor Paul Jose analyses into mainstream behavioral research. received his Ph.D. in Developmental Psychology Thursday, 4:30 pm - 6:00 pm from Yale University in 1980, and after a post- (Event 1-016) Reception doctoral fellowship at the Grand Salon EF Foyer University of Illinois, 4:30 pm – 6:00 pm Champaign-Urbana and teaching at Loyola University Chicago for 17 1-016. Welcome Reception years, currently teaches All attendees are encouraged to come! Please and conducts research on adolescent join us for wonderful hors d’oeuvres and an development and family dynamics at Victoria open bar. University of Wellington in New Zealand. His current research focus is positive youth development and the role of savoring and Friday, 7:30 am - 8:00 am mindfulness in positive functioning. In the domain of methodology and statistics he is currently (Event 2-001) Coffee writing a book, How to do statistical mediation Grand Salon EF Foyer and moderation (Guilford Press), and is working 7:30 am – 8:00 am on a stand-alone statistical program to compute mediation and moderation with raw data named 2-001 Coffee and Continental Breakfast M&M.

Friday, 8:00 am - 11:45 am (Event 2-003) Invited Workshop (Event 2-002) Invited Workshop Grand Salon B Grand Salon A Friday, 8:00 am - 11:45 am Friday, 8:00 am - 11:45 am 2-003. Network and Behavior Dynamics: An 2-002. How to do Statistical Mediation and Introduction in SIENA and Its Applications Moderation Instructor: René Veenstra Instructor: Paul E. Jose Abstract. Social relations can have a profound Abstract. This workshop is intended to acquaint impact on human development in all life stages, researchers with the core statistical concepts and be it positive relations such as friendship, methods of statistical mediation and moderation, support, and trust, or negative relations such as

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dislike, envy, and bullying. The totality of selection and influence dynamics, I will address relationships of a given type, measured in a additional questions treated in the SIENA meaningfully delineated social group, can be literature, such as questions about deselection represented by a social network. When networks dynamics and about moderation and mediation are used for explaining individual development, it processes in network and behavior dynamics. I needs to be considered that they also can finish with an outlook on future developments of develop over time. Together with the individual this approach. characteristics that change over time, the network change constitutes a mutually dependent Biography. René feedback process. On the one hand, Veenstra, Ph.D., is characteristics of individuals, pairs of individuals, Professor, Department of and structural positions of individuals within Sociology and networks can affect the evolution of the network. Interuniversity Center for The best-known example of such dependencies Social Science Theory for selection processes may be the homophily and Methodology (ICS), process: the formation of a relationship based on University of Groningen, the similarity of two individuals. On the other the Netherlands, Visiting hand, networks can affect the individual Professor, Department of characteristics and behavioral development of Psychology, University of their members. These latter dependencies can be Turku, Finland. During summarized as influence processes. A prominent the period 2011-2014, he coordinates the example is the assimilation process, by which implementation and evaluation of the KiVa socially connected individuals become Antibullying Program in the Netherlands. He increasingly similar over time. Because homophily published on a variety of topics (bullying and and assimilation result in the same empirical victimization, peer relations, prosocial and phenomenon (similarity of connected antisocial behavior, social network analysis, individuals), developmental researchers have temperament-by-environment interactions) in known for long that the study of influence major scientific journals including Child requires the consideration of selection, and vice Development, Developmental Psychology, versa. Any attempt to analytically separate International Journal of Behavioral Development, selection and influence processes is complicated Journal of Early Adolescence, Journal of Research by the fact that network data are inherently on Adolescence, and Social Networks. He is interdependent. Whether two individuals are Associate Editor of the Journal of Research on connected in a network can crucially depend on Adolescence for the period 2010-2016. For that their relations to third parties. Only few journal he edits, together with Jan Kornelis statistical methods are capable of mapping (or at Dijkstra, Christian Steglich and Maarten Van Zalk, least controlling for) such network dependencies. a special issue on Network and Behavior Dynamics Among these, the prominent tool for the analysis in Adolescence. of longitudinal network data is software called SIENA, Simulation Investigation for Empirical Network Analysis. It has proven to be a useful (Event 2-004) Invited Workshop analytic tool for questions about selection Grand Salon C (friends change but behavior stays similar) and Friday, 8:00 am - 11:45 am influence (friends stay similar but behavior changes) effects, with as strengths that it models 2-004. My First Bayes: Why and How to Run unobserved changes between observation points, Your First Bayesian Model Using Mplus controls for network structure effects, and takes Instructor: Rens van de Schoot dependencies in the data into account. In this presentation, I portray this method by first Abstract. Did you ever wonder why: (1) A p-value deriving some methodological requirements for of .049 is significant and whether a p-value of analyzing selection and influence dynamics, then .051 isn’t? (2) You are testing the null hypothesis giving a brief sketch of the model and indicating even when it is never among your hypotheses of how it meets these requirements. Next, interest? (3) It is sometimes difficult to interpret developmental applications and an illustration of the results of classical hypothesis testing? Did you the method are given. Besides questions about ever encounter one of the following issues: (1) A

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data set too small for your complex model? (2) expert knowledge to decide whether you should Non-normally distributed variables? (3) Negative switch to Bayesian statistics or not. variances or correlations larger than one? Or did you ever want to compute: (1) The probability Biography. Dr. Rens van de that your hypothesis is correct after observing Schoot first studied medical the data? Note that this is not the interpretation imaging techniques and of the classical p-value. (2) A 95% probability that worked for two years in the your estimate (e.g. mean, regression coefficient) university hospital of is in between two values? Note that, again, this is Utrecht. After this, he not the interpretation of the classical confidence completed his Psychology interval. (3) A degree of support for each of the bachelor with a minor in models in your model selection competition? If Juvenile Delinquency and you answered ‘yes’ to one of these questions, graduated cum laude for this workshop might be of interest for you! During the Research Master this one-day workshop you will be introduced to Development and Bayesian statistics. Bayesian statistics are Socialization of Children and Adolescents at the becoming more and more popular among applied Graduate School for Social Sciences at Utrecht researchers to answer the research question at University. He obtained his PhD about informative hand. This is especially due to the availability of hypotheses and Bayesian statistics at the Bayesian estimation methods in popular software Department of Methods and Statistics. While like MlWiN, AMORS or Mplus v6.x. The workshop obtaining his PhD, he was chair of the University will deal with four topics: First you are Board of PhD Students. He finished his PhD cum introduced into the world of Bayesian statistics. laude after only working three years on the This includes: Bayes theorem, P(H|data} versus project and was able to publish several articles as P{data|H), choosing prior distributions, a PhD student. Currently, he is working in the interpreting posterior distributions and what to Methods and Statistics Department, Utrecht do with posterior estimates. Second, we will University. Besides his research on how to discuss why one should switch to Bayesian directly evaluate expectations, he collaborates statistics. As Walker, Gustafson, and Frimer with many developmental researchers from (2007, p. 366) state “the Bayesian approach different fields on projects about identity offers innovative solutions to some challenging development, immigrants and post-traumatic analytical problems that plague research in [...] stress. Also, he takes part in different projects psychology". There are basically two reasons for about the labor market position of PhD students. switching: (1) you just like the definition of Finally, he is president of the Young Researchers Bayesian probability, or (2) Bayesian statistics Union of the European Association of can deal with some common encountered Developmental Psychology and he is vice-chair for problems in maximum likelihood estimation. Both the Scientific Committee of the Dutch Institute reasons will be discussed in detail. Third, you will for Psychologists (NIP). learn to analyze simple (regression) and more complex models (SEM/multi-level) using Bayesian Friday, 8:00 am - 9:45 am statistics available in Mplus. Lastly, I will also show that the Bayesian toolbox should not be (Event 2-005) Paper Symposium used carelessly. All textbooks introducing Grand Salon D Bayesian statistics warn users never to forget to Friday, 8:00 am - 9:45 am inspect the trace plots. In the current workshop it is shown why you should always do so, i.e. to 2-005. Eyes as windows of cognition: inspect convergence problems. This requires Developing eye-tracking techniques to expert knowledge of Bayesian statistics, and that understand infants’ developing control of is exactly what will be taught in the workshop. attention Moreover, guidelines are provided on how to Chairs: Erik Thiessen, Anna Fisher change the settings of the Mplus in such a way Carnegie Mellon University that convergence can be reached, but we also discuss that non-convergence might be a sign of  Distinct processes in infants’ perception of other problems with the model. All in all, after animate motion revealed by eye tracking attending this workshop, you will have enough

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Willem Frankenhuis, Bailey House, H Clark Friday, 10:00 am - 11:45 am Barrett, Scott Johnson UCLA (Event 2-007) Paper Symposium Grand Salon D  New Paradigms for Assessing Selective Friday, 10:00 am - 11:45 am Sustained Attention in Children and Analyzing Smooth Pursuit Eye Movements 2-007. Modeling Complexities of Behavioral John Dickerson, Lucy Erickson, Erik Thiessen, Process: The Leading Edge of EMA & Diary Anna Fisher Data Analysis Carnegie Mellon University Chairs: Nilam Ram, Peter Molenaar Pennsylvania State University  So much to look at: Eye tracking as a way of assessing online learning in more ecologically  Modeling Dynamics in Unequally Spaced Data: valid settings EMA Applications Natasha Kirkham, Rachel Wu, Kristen Swan Lawrence Lo, Peter Molenaar, Michael Birkbeck College, University of London Rovine, Nilam Ram Pennsylvania State University

 Measuring the Whole-Body Dynamics of Visual Attention in Toddlers  Using the Cubic Spline Model as a Data Linda Smith, Chen Yu, Damian Fricker Interpolation Tool Indiana University Diane Losardo, Sy-Miin Chow University of North Carolina

(Event 2-006) Paper Symposium  Issues in Aggregating Time Series: Illustration Meeting Room 12 Through an AR(1) Model Friday, 8:00 am - 9:45 am Zhiyong Zhang, Zhenqiu Lu University of Notre Dame 2-006. Intensive Data Collection Methods for Measuring Children’s Use of and  Linear and Nonlinear Regime-Switching State- Attention to Television and Other Space Models Electronic Media Sy-Miin Chow, R. Hutton, Diane Losardo University of North Carolina Chair & Discussant: David Bickham

Children's Hospital Boston  The Use of Eye-Tracking Methodology to (Event 2-008) Invited Talk Study Online Processing of Video Meeting Room 12 Heather Kirkorian Friday, 10:00 am - 11:45 am University of Wisconsin-Madison 2-008. Theoretical Models, Statistical  Method for Assessing Reliability and Validity Models, and Testing Conjectures Strongly of Intensively Collected Media Use Measure in Chair: Todd D. Little the Measuring Youth Media Exposure (MYME) Invited Speaker: Keith Widaman Study Emily Blood, David Bickham, Lydia Shrier, Abstract. Hypothesis testing in psychology in Michael Rich general and in developmental psychology in Children's Hospital Boston particular typically follows a routinized procedure: A theoretical model leads to predicted patterns in data, data are collected, a  Converging Operations: The Utility of a Multi- statistical analysis approach is selected, a null Method Developmental Approach to Studying hypothesis is formulated, and a statistical test is Infants and Media conducted to reject the null hypothesis and claim Deborah Linebarger1, Rachel Barr2 1 2 that the theoretical model and its conjectures University of Iowa; Georgetown University are thereby supported. Despite its widespread use, several problems can be identified with this procedure. One problem is the logic of the

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significance test itself, which tests the converse environment, or GXE, interactions. I will also of the theoretical prediction, not the theoretical discuss general ways to generalize this approach prediction itself. A second problem is the lack of to our most commonly used methods of analysis, specificity with regard to the theoretical so that we do what we set out to do - test our hypothesis or conjecture guiding the research and theoretical predictions. the corresponding lack of specificity of the information obtained from the test of Biography. Keith Widaman significance. Paul Meehl often referred to the is a Distinguished Professor lack of specificity in hypotheses as the flabbiness in the Department of of our predictions - with flabby predictions Psychology at the University leading to flabby tests of significance, which of California, Davis. He contribute to the slow progress in many areas of received his Ph.D. in 1982 psychology. The preceding, standard approach to from the Ohio State data analyses is exploratory in nature, which University in Developmental might be seen as its greatest strength, but may Psychology, with a minor in also be regarded as its principal shortcoming. On Quantitative Psychology. the positive side, a data analyst need know Widaman has interests in nothing about the hypotheses motivating the multivariate linear models, study. The analyst can simply ask which analytic including regression analysis, factor analysis, procedure is to be used (t-test, ANOVA, structural equation modeling, and the modeling regression, etc.), which variables are of longitudinal data. His substantive research independent variables, which variable is the focuses on family, economic, and other dependent variable, and the analysis can proceed influences on child development and the - without the analyst ever having to learn about development of mental abilities and skills in both what the variables mean, what theory led to the representative and developmentally disabled collection of data, etc. The analyst can provide populations. His work has appeared in methods- precise statistics for each significance test (test oriented journals such as Psychological Methods statistic, p-value, etc.), and the substantive and Multivariate Behavioral Research, and in psychologist supplies the understanding to go substantive journals such as Developmental with the statistical results. Is there a negative Psychology, Child Development, and Intelligence. side? A negative side does exist if other, more Widaman has served on the Editorial Boards of informative ways are available for testing our many journals, including Psychological Methods, conjectures strongly. I argue that we should Multivariate Behavioral Research, Intelligence, incorporate confirmatory approaches into our and Structural Equation Modeling. He is a Fellow analyses. Confirmatory approaches begin with of the American Psychological Association clear and definitive predictions derived from our (Divisions 5, 7, and 33) and the Association for theories. We should not be content with theories Psychological Science. Widaman received the that predict merely that differences should be 1992 Raymond B. Cattell Award for early career found. Instead, our theories should state whether contributions to multivariate psychology from the certain trends should be present (e.g., linear, Society of Multivariate Experimental Psychology quadratic) and perhaps even delineate some (SMEP), has twice received the Tanaka Award for conjectures about magnitudes of parameter best article in SMEP’s journal Multivariate estimates. Then, statistical models can be Behavioral Research, and is a Past President of formulated that embody the theoretical SMEP. predictions precisely, and the theoretical predictions should be tested strongly to Friday, 1:30 pm - 3:15 pm determine whether they are consistent with the data. I will provide examples for confirmatory (Event 2-009) Paper Symposium analytic approaches from several substantive Grand Salon A domains, including estimating prenatal influences Friday, 1:30 pm - 3:15 pm on intelligence of children of mothers with PKU, modeling growth trends for adaptive behaviors of youth with developmental disabilities, and comparing predictions of diathesis-stress and differential susceptibility models for gene X

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2-009. Time and Place: Exploring the Eric Duku1, Magdalena Janus1, Sally Statistical Modeling of Developmental Brinkman2 1Offord Centre for Child Studies, McMaster Processes over Time with Setting-Level 2 Features as Predictors University; Telethon Institute for Child Health Research Chair: Stephanie Jones Harvard University  Modeling Individual Differences in Within- Person Variation in a Mixed Effects Location  Seasonal Change in Developmental Scale Model Trajectories of Aggression: A test of Philippe Rast, Scott Hofer Developmental-Contextual Models 1 1 University of Victoria Andres Molano , Stephanie Jones , Joshua 2 3 Brown , J. Lawrence Aber 1Harvard University; 2Fordham University;  Measurement Equivalence of a Screener for 3New York University Behavioral and Emotional Risk across Language Form Bridget Dever, Randy Kamphaus, Tara Raines  The Classroom as a Complex System: Georgia State University Modeling the Association Between Classroom Climates and Teacher-child Relationships Over Time (Event 2-011) Paper Symposium Catalina Torrente2, J. Lawrence Aber2, Grand Salon C Stephanie Jones1, Joshua Brown3 Friday, 1:30 pm - 3:15 pm 1Harvard University; 2New York University; 3Fordham University 2-011. Emerging Longitudinal Methods for Studying the Development of Antisocial  Mothers’ Anxiety over Time: A Longitudinal Behavior Analysis Examining the Role of Child, Family, and Neighborhood Characteristics in Chair: Thomas Loughran Predicting Maternal Anxiety Trajectories University of Maryland 1 1 Hadas Eidelman , Stephanie Jones , Alice  Describing Trajectories of Adolescent 2 Carter Antisocial Behavior with Accelerated 1 2 Harvard University; University of Longitudinal Data: Analytic and Matching Massachusetts – Boston Methods Christopher Sullivan2, Thomas Loughran1 1University of Maryland; 2University of (Event 2-010) Constructed Paper Symposium Cincinnati Grand Salon B Friday, 1:30 pm - 3:15 pm  Linking Variability in Subjective Risk 2-010. Examples of Evaluating Perception Updating to Adolescent Cognition: Measurement in Longitudinal and Cross- A Random Coefficient Model of Bayesian Risk Updating National Studies Thomas Loughran Chair: Scott M. Hofer University of Maryland University of Victoria  Emotional Security Among Chinese Families:  A Propensity Score Model for the Treatment Validation of the Security in the Interparental Effect of Adolescent Maltreatment on Subsequent Maltreatment Perpetration Subsystem Scales 1 2 1 2 Terrence Thornberry , Kimberly Henry Rebecca Y. M. Cheung , Yan Li , E. Mark 1 2 Cummings1 University of Maryland; Colorado State 1University of Notre Dame; 2DePaul University University

 Investigating Cross-national Equivalence of a  Are high-anxious variants of youth with Measurement of Early Child Development psychopathic traits more violent across time Outcomes

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compared with low-anxious variants and 2-013. Methodological Advances in the youth scoring low on psychopathy? Study of Executive Function Development Eva Kimonis University of South Florida Chair: Stephanie Carlson University of Minnesota  Understanding Executive Function in Early (Event 2-012) Paper Symposium Childhood: Insights from Confirmatory Factor Grand Salon D Analysis Friday, 1:30 pm - 3:15 pm Sandra Wiebe1, Jennifer Nelson2, Tiffany 2 2 2-012. Comparing methods for modeling Sheffield , Nicolas Chevalier , Craig Johnson2, Kimberly Espy3 excess zero values in longitudinal analyses 1University of Alberta; 2University of of behavioral outcomes Nebraska; 3University of Oregon

Chair: Craig Henderson1  Scaling the Development of Executive Discussant: Hanno Petras2 Function in Preschool Children 1Sam Houston State University; 2JBS Stephanie Carlson International, Inc. University of Minnesota  “Simple” models for longitudinal data with excess zeros: Censored, zero-inflated, and  NIH Toolbox Cognitive Function Battery two-part growth curves (NIHTB-CFB): Measuring Executive Function 1 2 and Attention Daniel Feaster , Kimberly Henry , Paul 1 1 Greenbaum3, Wei Wang3, Hanno Petras4, Philip Zelazo , Jacob Anderson , Jennifer 5 6 Richler2, Kathleen Wallner-Allen3, Jennifer Katie Witkiewitz , Juan Pena 4 4 1University of Miami; 2Colorado State Beaumont , Sandra Weintraub 3 4 1University of Minnesota; 2Indiana University; University; University of South Florida; JBS 3 4 International, Inc.; 5Washington State Westat; Northwestern University University; 6Washington University  Modeling the Experiential Canalization of  Growth mixture modeling with and without a Executive Function in Early Childhood: How “zero class” Does a Fixed Effect Approach Stack Up? M. Lee Van Horn2, Shaunna Clark1, Hanno Clancy Blair, C Cybele Raver Petras3, Karen Nylund-Gibson4, Juan Pena5 New York University 1Virginia Commonwealth University; 2University of South Carolina; 3JBS Friday, 3:15 pm - 3:30 pm International, Inc.; 4University of California at Santa Barbara; 5Washington University (Event 2-014) Afternoon Break Grand Salon EF Foyer 3:15 pm – 3:30 pm  Using a joint survival-to-growth model for the study of time-to-initiation and trajectories of alcohol use in adolescence 2-014 Afternoon Refreshments Katherine Masyn1, Patrick Malone2, Katie 3 4 Witkiewitz , Juan Pena Friday, 3:30 pm - 4:30 pm 1Harvard University; 2University of South Carolina; 3Washington State University; 4 (Event 2-015) Plenary Session Washington University Grand Salons E-F Friday, 3:30 pm - 4:30 pm

(Event 2-013) Paper Symposium 2-015. Past Lessons and Future Directions Meeting Room 12 of Developmental Methodology Friday, 1:30 pm - 3:15 pm Co-Chairs: Noel A. Card, Todd D. Little Keynote Speaker: Margaret (Peg) Burchinal

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Abstract. During the past 40 years, children, and is a leading contributor to this developmental methodology has broadened from literature. being primarily focused on experimental designs to encompassing almost all aspects of Friday, 4:45 pm - 6:00 pm developmental science. The advent of accessible fast computers and the advances in statistical (Event 2-016) Poster Session with Refreshments methods led to a plethora of methodologies that Grand Salons G-J range from item response theory for more precise Friday, 4:45 pm - 6:00 pm measurement to structural equation models for representing complex theoretical models. 1 Test Scaling in Cognitive Development: Methods for describing change over time have For Some Elementary Processes, One advanced from very restrictive approaches to Need Not Adjust Test Difficulty very flexible methods within structural equation Nelson Cowan modeling and hierarchical linear models. Multi- University of Missouri disciplinary teams within developmental research led to increased focus on methods that reduce 2 Temperament and Gender Differences in selection bias in analyzing observational data and Toddlers Born Preterm on methods that can combine our understanding Maria Beatriz Linhares, Luciana Rocha, from both qualitative and quantitative analyses. Vivian Klein Examples of how developmental methods have University of São Paulo changed will be provided and attempts will be made to discuss past lessons and suggest future 3 Scale Invariance in the Measurement of directions. Mental-attentional Capacity

Juan Pascual-Leone, Janice Johnson Biography. Dr. Burchinal York University is Senior Scientist and Director of the Data Management and 4 Simulating Reliability for Nominal Data: Statistics Core at the Cohen's Kappa is Biased, the Novel FPG Child Development Agreement Statistic Iota is Consistent Institute at the With Pivotal Properties of Reliability Rho University of North Gregor Kappler Carolina at Chapel Hill University of Vienna and Adjunct Professor of Education at the 5 Confirmatory Factory Analysis with Count University of California- Variables: Implications for Significance Irvine. She is currently an associate editor for Testing of Nested Models when Indicators Child Development and Early Childhood Research are Not Normally Distributed 1 2 Quarterly, and has been a member of is a R. Barker , Rose Sevcik 1 2 member of The Secretary’s Advisory Committee University of Kansas, Georgia State for Head Start Research and Evaluation. She University served as the primary statistician for many educational studies of early childhood, including 6 The self-evaluations scales of relationship Abecedarian project, Cost, Quality and Outcomes and motivation (REMO) in school: Study, and the NICHD Study of Early Child Care. development of a measure As an applied methodologist, she helped to William Bukowski2, Diana Raufelder1, demonstrate that sophisticated methods such as Danilo Jagenow1 meta-analysis, fixed-effect modeling, 1Free University Berlin, 2Concordia hierarchical linear modeling, piecewise University regression, and generalized estimating equations provide educational researchers with advanced 7 Quantitative ethnography and the study techniques to address important issues for of development within context research and policy. In addition, she has pursued William Bukowski, Diana Raufelder her substantive interest in early education as a Concordia University means to improve school readiness for at-risk

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8 Alternative Factorial Invariance Models the Transition to Adulthood: A Systematic for Teachers' and Students' Ratings of Review School Culture Kara Thompson, Timothy Stockwell Ping Guo1, Yan Zhou2, Ann Higgins- University of Victoria D'Alessandro1 1 2 Fordham University, University of 16 Prediction of Change under Alternative Southern California Codings of Time Catharine Sparks1, Andrea Piccinin1, Lesa 9 Withdrawn Hoffman2, Scott Hofer1 1University of Victoria, 2University of 10 Using a Longitudinal Multiple-Group APIM Nebraska-Lincoln for Distinguishable Partners to Investigate Patterns of Friend Influence 17 An Illustration of Follow-up Tests for Donna Marion1, Brett Laursen1, Katariina Growth Curve Modeling Using Salmela-Aro2, Noona Kiuru3, Jari-Erik Longitudinal Depression and Intoxication Nurmi3 Frequency Data 1Florida Atlantic University, 2University of Ashley Richmond, Brett Laursen, Dawn Helsinki, 3University of Jyväskylä DeLay, Shrija Dirghangi, Cody Hiatt, Daniel Dickson, Amy Hartl 11 Classroom Quality: A Multilevel Structural Florida Atlantic University Equation Modeling Approach to Understanding the Relationship Between 18 Assessing Early Child Development in the Preschool Environments and Verbal Skill East Asia Pacific Region: Cultural Development Appropriateness and Item Equivalence in Adam Holland1, Chelsea Burfeind2 Measurement 1 1 2 1University of North Carolina at Chapel Jin Sun , Nirmala Rao , Patrice Engle 1 2 Hill, 2University of North Carolina at The University of Hong Kong, California Chapel Hill Polytechnic State University

12 Multi-facet Longitudinal Modeling of 19 Everything but the “Kitchen Sink”: Using Adolescent Alcohol Use: Enabling Novel Second-Order Confirmatory Factor Findings on Ethnicity and Gender Analysis to Inform Measurement of Differences Parenting Quality Patrick Malone1, Andrea Lamont1, Elizabeth Plowman, Angela Narayan, Katherine Masyn2 Janette Herbers, Ann Masten 1University of South Carolina, 2Harvard University of Minnesota Graduate School of Education 20 Integrative Data Analysis: Aggregating 13 Longitudinal Factor Structure of the Federally Funded and Public Use Datasets Cyber Aggressions/Victimization For Examining Parenting Processes and Questionnaires among Adolescents and Youth Outcomes 2 1 Young Adults Nancy Whitesell , Akira Kanatsu , Diane 1 5 4 Michelle Wright Hughes , Ruth Chao , Nancy Hill , Huynh- 3 DePaul University Nhu Le 1New York University, 2University of 3 14 The Inventory of Peer-Nominated Cyber Colorado, Denver, George Washington University, 4Harvard University, Behaviors: Measurement Equivalence 5 Across Time University of California, Riverside Michelle Wright DePaul University 21 Trajectories of Accumulated Risk During the Transition from Middle Childhood to 15 Using Multiple-Group Methods to Study Early Adolescence and Their Outcomes the Development of Alcohol Use Across Elizabeth Hall, Libo Li, Christine Grella University of California, Los Angeles

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22 Comparison of Growth Curve Modeling 29 Do Fierce Birds Flock Together?: and Group-Based Modeling to Study the Homophily of Interpersonal Aggression in Development and the Predictors of Emerging Adult Ego Networks Cognitive Functions Michelle Little Mathieu Pilon1, Charles-Édouard UTSA Giguère1, Sophie Parent2, Philip Zelazo3, 1 1 Richard Tremblay , Jean Séguin 30 Automated Measurement of Infant Head 1 CHU Sainte-Justine Research Center, Orientation in Infant Negotiation of 2 Ecole de psychoeducation, Universite de Relational Space 3 Montreal, Institute of Child Mette Vaever Development, University of Minnesota University of Copenhagen

23 How to Choose the Best Developmental 31 It’s About Time: Revealing the Dynamic Model: Examples From Numerical Interplay Among Children’s Exuberance Estimation Characteristics in Unstructured Group Christopher Young, John Opfer Play Ohio State University Adriene Beltz, Charles Beekman, Peter Molenaar, Kristin Buss 24 Here’s Looking at You: Quantifying Pennsylvania State University Quotidian Exposure to Faces in Young Infants and Adults. 32 Using the Internet for Developmental Nicole Sugden, Margaret Moulson Research Ryerson University Sam Hardy Brigham Young University 25 Measuring Interpersonal Conflict: How Measurement Scale, Reference Period 33 Dynamic Modeling of Infant-Caregiver and Memory Cues Influence Conflict Interactions during the Face-to-Face Still- Reports Face Paradigm using the State Space Grid Shrija Dirghangi, Dawn DeLay, Justin Technique Puder, Brett Laursen, Amy Hartl, Daniel Akhila Sravish1, Ed Tronick1, Tom Dickson, Ashley Richmond, Cody Hiatt Hollenstein2, Marjorie Beeghly3 Florida Atlantic University 1University of Massachusetts Boston, 2Queen's University, 3Wayne State 26 Measurement of Early Father Involvement University using Time Diary Data and Associations with Parents’ Prenatal Depression and 34 CUE: The Continuous Unified Electronic Empathy Diary Method Rongfang Jia, Letitia Kotila, Sarah Kate Ellis-Davies, Elena Sakkalou, Nia Schoppe-Sullivan, Claire Kamp Dush Fowler, Elma Hilbrink, Merideth Gattis The Ohio State University Cardiff University

27 Methods of Analyzing Observed Behavior: 35 Withdrawn A Comparison of Rates, Proportional Responses, and Contingencies 36 Identifying Profiles of Risk for Youth in Diane Putnick, Marc Bornstein Contexts of Political Violence NICHD Christine Merrilees1, Laura Taylor1, Kalsea Koss1, Marcie Goeke-Morey2, Peter 3 4 1 28 Micro Change Processes in Dyadic Shirlow , Ed Cairns , E. Mark Cummings 1 2 Coordination During Early Mother Infant University of Notre Dame, Catholic 3 Interaction University of America, Queens 4 Susanne Harder, Simo Koeppe, Mette University, University of Ulster Vaever University of Copenhagen

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37 Using Derivatives to Examine Individual 44 A Method For Signal Detection and Difference in Affect Structure Over a Quantification of Heart Rate Data in Burst of 56 Days of Measurement in Late Human Research: Insights From Adulthood Engineering and Psychology Monica Erbacher1, Karen Schmidt1, Cindy He Ba, Li Chen, Wendi Heinzelman, Bergeman2 Zeljko Ignjatovic, Melissa Sturge-Apple 1University of Virginia, 2University of University of Rochester Notre Dame 45 A New Gaze Contingent Eye Tracking Task 38 A dynamic systems approach to for the Assessment of Reward integrating dyadic physiology and Reinforcement Value observed interaction behaviors in the Carolyn McCormick, Gregory Young, Sally study of maternal depression and family Rogers functioning. University of California, Davis Arin Connell, Abigail Hughes-Scalise, Susan Klostermann 46 The Baby Care Questionnaire: A Reliable Case Western Reserve University Measure of Parenting Principles and Practices 39 Actor Partner Interdependence model for Alice Winstanley, Merideth Gattis integrating Respiratory Sinus Arrhythmia Cardiff University and affective dynamics during parent- adolescent interactions 47 The essential messiness of group Arin Connell, Abigail Hughes-Scalise, matching in autism research: Taking up Susan Klostermann the challenge in the name of empirical Case Western Reserve University precision Vanessa Babineau, Stephanie Rishikof, 40 A Validity Perspective of Developmental Colin Campbell, Jacob Burack Methodology: Assessing Narrative McGill University Comprehension Processes in All Young Children 48 A comparison of two measurement Marcia Calloway, Chastity McFarlan, technologies to collect electrodermal Danielle Brown activity in infants Howard University Jennifer DiCorcia1, Matthew Goodwin2, Nancy Snidman1 1 41 Assessing Feelings of Belonging in School: Childrens Hospital/Harvard Medical 2 Addressing the Problem of Confounded School, MIT Media Lab Item Content Molly Weeks1, Steven Asher1, Kristina 49 Nominating Under Constraints: McDonald2 Differences Between Limited and 1Duke University, 2University of Alabama Unlimited Sociometric Measurements Rob Gommans, Antonius Cillessen 42 An Item Response Model for Home Radboud University Language Preference Surveys Lee Branum-Martin, Paras Mehta, David 50 Do Callous/Unemotional Traits Subtype Francis Childhood Conduct Problems? A Meta- University of Houston Analytic Review of the Literature Sarah Haas1, Daniel Waschbusch2 1 2 43 Coparenting Observations of Lesbian, University at Buffalo, Florida Gay, and Heterosexual Adoptive Couples: International University Reflections on the Coparenting Behavior Coding Scale 51 An interdisciplinary challenge: method Rachel Farr1, Charlotte Patterson2 triangulation in the field of brain 1University of Massachusetts Amherst, development and motivation 2University of Virginia

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Diana Raufelder1, William Bukowski2, 58 Accuracy of Retrospective Data Vary by Danilo Jagenow1 Developmental Content, Person, and 1Free University Berlin, 2Concordia Metric of Agreement University Marc Bornstein, Diane Putnick, Joan Suwalsky, Mariya Sumaroka 52 Re-parameterizing Regression Models to NICHD Test Theoretically Important Conjectures: The Sample Case of Gene X 59 Longitudinal Models for Assessing Environment Interactions Dynamic Relations: Children’s Anxious Keith Widaman1, Jonathan Helm1, Laura and Depressive Symptoms Castro-Schilo1, Michael Pluess2, Michael Chrystyna Kouros1, Lauren Papp2, Judy Stallings3, Jay Belsky2 Garber3 1University of California, Davis, 1Southern Methodist University, 2University of California, 3University of 2University of Wisconsin-Madison, Colorado 3Vanderbilt University

53 Adolescent peer groups and their 60 Identifying and recruiting a random influence on behaviors: Does sample from a population who do not measurement make a difference? participate in early childhood services. Lorrie Schmid1, Megan Golonka2 Daniel Cloney1, Karen Thorpe2, Collette 1University of North Carolina - Chapel Tayler1 Hill, 2Duke University 1The University of Melbourne, 2Queensland University of Technology 54 Measuring Emotion Regulation in Field- Based Settings: Understanding the Dot 61 Multilevel Poisson Models for Children’s Probe Task Longitudinal Sociometric Rating Data Alexandra Ursache, Amanda Roy, C Richard Faldowski1, Heidi Gazelle2, Cybele Raver Tamara Spangler Avant3 New York University 1University of North Carolina at Greensboro, 2University of Melbourne, 55 A Multilevel Confirmatory Factor Analysis 3South University with Covariates to Assess the Factorial Validity of the Scores on the Student- 62 Exploring the biometric dual change score Teacher Relationship Scale-Short Form model in the development of reading 1 Mi-young Webb , Stacey Neuharth- component processes 2 Pritchett Sara Hart, Christopher Schatschneider, 1 2 Georgia State University, University of Jeanette Taylor Georgia Florida State University

56 Multi-level factor analysis (MLFA): An 63 A Bayesian Approach to Measurement emerging method to measure Invariance Tests in Longitudinal Research environments using individual-level data on Executive Control across the Preschool without aggregation Years 1 2 Erin Dunn , Katherine Masyn Caron Clark, Hye-Jeong Choi, Tiffany 1 Harvard School of Public Health, Sheffield, Kimberly Espy 2 Harvard Graduate School of Education University of Nebraska-Lincoln

57 GEEs get more from your data: Using 64 Using Lagged Dependent Variables in generalized estimating equations with Developmental Research: Understanding high repeated measures and small sample the Problems and Providing Solutions sizes Jade Marcus1, E. Foster2 1 2 Dorothy Mandell , Emily Blumenthal 1UNC-Chapel Hill, 2University of Alabama 1 2 University of Amsterdam, University of at Birmingham California, San Diego

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65 On the Coding of Time for Growth Curve 72 Enrichment Programs and Long-term Modeling: Impact of Imposing Effects of Early Interventions: New Rectangularity on Non-Rectangular Data Evidence from a Randomized Trial in Sets Head Start Settings Peggy Keller, Sarai Blincoe Fuhua Zhai1, C Cybele Raver2 University of Kentucky 1Stony Brook University, 2New York University 66 Biobehavioral Pain Reactivity-Recovery Profiles in Preterm Infants 73 The effect of kindergarten entry age on Beatriz Valeri, Claudia Gaspardo, non-cognitive outcomes: An instrumental Francisco Martinez, Maria Beatriz variables approach Linhares Michael Gottfried1, Ashlesha Datar2 University of Sao Paulo 1Loyola Marymount University, 2RAND Corporation 67 A Better Fit: Using Structural Equation Modeling to Examine Transactional 74 Improving Evidence of Causal Mediation Pathways of Family Involvement and with Residualized and Simple Gain Scores Student Achievement Robert Larzelere, Kami Schwerdtfeger, Christina Cipriano Ronald Cox Northeastern University Oklahoma State University

68 Overestimation of the Number of Groups 75 Considering Sensitive Periods in in Mixture Model Analyses in Presence of Development with Three-Wave a Misspecified Covariance Matrix Longitudinal Data 1 Charles-Édouard Giguère1, Jean Séguin2 Thomas Fuller-Rowell , Jacquelynne 2 2 1Université de Montréal, 2Université de Eccles , Amanda Brodish , Courtney 2 2 Montréal Cogburn , Steve Peck , Oksana 2 Malanchuk 1University of Wisconsin--Madison, 69 Whether and When Children with 2 Complex Health Problems Experience University of Michigan Parental Separation? An Application of Survival Analysis to Developmental 76 Intergenerational Continuity of Emotional Research Abuse: A Person-Oriented Approach to Rubab Arim1, Dafna E. Kohen1, Rochelle Parenting under Stress Garner1, Lucyna Lach2 Courtney McCullough, Rachel Han, Hilary 1Statistics Canada, 2McGill University Harding, Melissa Bright, Anne Shaffer University of Georgia 70 Examining the Longitudinal Measurement Equivalence of a Parenting Scale across 77 Implementation of the Regression Three Age Groups from Childhood through Discontinuity Design with an Intervention Adolescence for Victims of Bullying. Rubab Arim1, Jennifer D. Shapka2, V. Christopher Harper, Christopher Henrich, Susan Dahinten2, Brent F. Olson2 Kristen Varjas, Joel Meyers 1Statistics Canada, 2University of British Georgia State University Columbia 78 Do You See What I See: Using Dyadic 71 The Implementation of Active Control Mediation to Answer Developmental Groups in Parent-based Interventions Questions 1 2 Jody Nicholson1, Jennifer Burke-Lefever3, Christopher Hafen , Dawn DeLay , Brett 2 Jaelyn Farris2, Carol Akai5, Shannon Bert4 Laursen 1 2 1St. Jude Children's Research Hospital, University of Virginia, Florida Atlantic 2Penn State Harrisburg, 3University of University Notre Dame, 4University of Oklahoma, 5Connecticut College

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79 Using a Structural Equation Model With Toddlers’ Self-Regulation and Maternal Interchangeable Dyads: Longitudinal Stress Study of Maternal Distress on Young Tiffany Martoccio, Holly Brophy-Herb Twin’s Representations Michigan State University Yeonsoo Yoo University of Connecticut 87 The Role of Family Processes between Parental Dysphoria and Adolescent 80 Father Involvement: The Effects of Adjustment: An 8-Year Longitudinal Study Fathers, Mothers, and Children Rebecca Y. M. Cheung1, Kalsea Koss1, E. Selva Lewin-Bizan Mark Cummings1, Patrick Davies2 Tufts University 1University of Notre Dame, 2University of Rochester 81 Unraveling Victim-Offender Overlap: Exploring Profiles and Constellations of 88 Bullying Perpetration and Sexual Risk Harassment in Adolescence: The Joan Reid1, Christopher Sullivan2 Moderating Role of Masculinity Beliefs 1University of South Florida, 2University Mrinalini Rao2, Todd Little1, Dorothy of Cincinnati Espelage2 1University of Kansas, 2University of 82 Using Policy as Design: Causal Effects of Illinois Age of Entry into Center Care in Norway by Instrumental Variable Analysis 89 Using Twin Modeling to Understand Henrik Zachrisson, Ane Narde Differing Patterns of Gene-Environment Norwegian Center for Child Behavioral Interplay Across Age and Reporter Development T. O'Brien1, Kathryn Lemery-Chalfant2, H. Goldsmith3 1 2 83 The Opportunity NYC-Family Rewards Northwestern University, Arizona State 3 Intervention: Comparing Program Impacts University, University of Wisconsin- Using Variable-Centered and Person- Madison Centered Approaches Sharon Wolf, Pamela Morris, J. Lawrence 90 Time-Varying Effects Model: Momentary Aber Health and Stress as Moderators of New York University Perception of Social Interactions Mariya Shiyko1, Nilam Ram2, Runze Li2, 2 2 84 A Triadic Extension of the Actor-Partner David Conroy , Aaron Pincus 1 2 Model: Examining Unique Effects of Northeastern University, Penn State Multiple Partners during a Family Problem-Solving Task 91 Exploring the concept and educational Kalsea Koss1, Melissa George2, Christine influence of preschool quality in Germany Merrilees1, Laura Taylor1, E. Mark and England Cummings1, Patrick Davies3 Yvonne Anders1, Pamela Sammons2, Hans- 1University of Notre Dame, 2University of Guenther Rossbach1, Kathy Sylva2, Sabine South Carolina, 3University of Rochester Weinert1 1University of Bamberg, 2University of 85 Latent Variable Interactions Demystified: Oxford A How-To for Their Estimation and Interpretation 92 Testing Measurement Equivalence and Julie Maslowsky1, John Schulenberg2 Stability in Longitudinal Data 1University of Michigan, 2University of Jenn-Yun Tein, George Knight, Mark Michigan Institute for Social Research Roosa, Katharine Zeiders, Rebecca White Arizona State University 86 Testing Transactional Models of Associations between Low-Income

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93 Event Frequency Measurement: Variance Vanderbilt University in Conflict Assessments are Differentially Associated with Depression 100 The Effects of Missing Time-Varying 1 2 Cody Hiatt , Karinna Vazquez , Justin Covariates in Multilevel Models 3 1 1 Puder , Amy Hartl , Daniel Dickson , Sierra Bainter 1 Brett Laursen The University of North Carolina 1Florida Atlantic University, 2Yeshiva 3 University, Auburn University 101 Differential specification of the bifactor model to control item dependency in 94 Recursive Estimation Approaches for reading comprehension. Estimating General Linear and General Yaacov Petscher Linear Mixed Models Florida Center for Reading Research Michael Rovine, Lawrence Lo, Peter Molenaar 102 The Superwoman/Black Female Ideal Pennsylvania State University Scale: An Intersectional Identity Development Measurement for Black 95 Longitudinal relations between Female Adolescents depression and conduct problems in girls: Celine Thompson An examination using parallel process University of Pennsylvania, Graduate latent class growth analysis School of Education Thomas Olino, Stephanie Stepp, Alison Hipwell, Rolf Loeber 103 Identifying Urbanicity-Related University of Pittsburgh Differences in the Relationship Between 96 Variability in Testosterone, Risk and Family Income and Early Achievement Resilience, and Externalizing Behaviors in Using Generalized Additive Modeling Adolescence Portia Miller1, Elizabeth Votruba-Drzal1, Melissa Peckins, Elizabeth Susman Claude Setodji2 Pennsylvania State University 1University of Pittsburgh, 2RAND Corporation 97 Multivariate longitudinal modeling of cognitive change: Relationship between 104 Bayes as a golden solution for all your processing speed and visuospatial ability 1 2 modeling issues? But, never forget to Annie Robitaille , Graciela Muniz , inspect the trace plot! Andrea Piccinin1, Boo Johansson3, Scott 1 Rens van de Schoot, Seda Can, Joop Hox Hofer Utrecht University 1University of Victoria, 2MRC Biostatistics Unit, 3University of Gothenburg 105 Within-and Between-Person Factor Structure of Positive and Negative Affect 98 Measurement Invariance for Parental Jonathan Rush, Catharine Sparks, Scott Autonomy Granting Constructs Among Hofer African American, White, and Hispanic University of Victoria Families Sharon Ghazarian1, Kathleen Roche2, Luisa Franzini3, Margaret Caughy4 106 Filtering Out Invalid Respondents Based 1Johns Hopkins University, 2Georgia State on the Analysis of Negative Statements in 3 Likert-scale Questionnaires University, University of Texas, 1 2 4University of Texas Krisztian Jozsa , George Morgan , Robert Pap-Szigeti3 1University of Szeged, 2Colorado State 99 Evaluating Longitudinal and Subgroup University, 3Kecskemet College Measurement Equivalence in a Battery of Cognitive Self-Regulation Measures for 107 Withdrawn Preschoolers Mary Fuhs, Kimberly Turner, Nianbo 108 A Multitrait-Multimethod Model to Dong, Mark Lipsey, Dale Farran Analyze Executive Functions: Taking into

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Account the Emotional Loading of the Carla Martins1, Ana Osório1, Eva Martins2, Stimulus Paula Castiajo1, Manuela Veríssimo3, Mauricio Garnier-Villarreal1, Luis Conejo- Isabel Soares1 Bolaños2 1University of Minho, 2Instituto Superior 1University of Kansas, 2University of Costa da Maia, 3ISPA - Instituto Universitário Rica 115 How Should the Narrative Goal Structure 109 Individual Differences in Forgetting: A Complexity of Narrative Stimuli be New Measurement of Forgetting Using Determined? Parceling Chastity McFarlan, Marcia Calloway, Tanja Kurtz, Daniel Zimprich Danielle Brown University of Erlangen-Nuremberg Howard University

110 Dynamic Relations Within and Between Saturday, 7:30 am - 8:00 am Early Communication Key Skill Elements over Time: Evidence of Contiguous (Event 3-001) Coffee Continuity in Skill Development Grand Salon EF Foyer Luke McCune1, Waylon Howard1, Charles 7:30 am – 8:00 am Greenwood2, Dale Walker2, Jay Buzhardt2, Rawni Anderson1 1University of Kansas, 2Juniper Gardens 3-001. Coffee and Continental Breakfast Children's Project Saturday, 8:00 am - 11:45 am

(Event 2-017) Ask-A-Question Poster Session (Event 3-002) Invited Workshop with Refreshments Grand Salon A Grand Salons G-J Saturday, 8:00 am - 11:45 am Friday, 4:45 pm - 6:00 pm 3-002. The Use of Integrative Data Analysis in Developmental Research 111 What are helpful data analytic approaches for analyzing and Instructors: Daniel J. Bauer, Andrea Hussong understanding trajectories of maternal Abstract. Integrative Data Analysis (IDA) is an depression in relation to infant affect emerging tool for integrating research findings expression? across studies through the simultaneous analysis Katherine Harris, Alissa Huth-Bocks of multiple independent data sets. Like other Eastern Michigan University such tools, such as substantive literature reviews, meta-analysis, and the independent but parallel 112 How Should we Measure and Model Types analysis of multiple studies, IDA has a primary of Discrimination for Adolescents? goal of synthesis and thus responds to the need Jessica Harding, Diane Hughes, Niobe for a cumulative approach to scientific inquiry. Way However, unlike these other tools, IDA provides a New York University means for directly comparing results across studies for novel scientific questions using the 113 What Statistical Analysis Can Reveal power of inferential statistics (in contrast to Different Types of Underlying Structures parallel analysis and substantive literature in Time Series Categorical Data? reviews) without relying on published findings of Kathy Ritchie questions only asked in prior studies (in contrast Indiana University South Bend to meta-analysis and substantive literature reviews). Although IDA is not appropriate in every 114 How to Account for Different Time context, when feasible the pooling of multiple Intervals Between Assessments in the datasets for IDA has the potential benefits of Same Longitudinal Sample? increased sample size (resulting in greater statistical power, particularly for group comparisons and tests of interactions) and sample

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heterogeneity (resulting in greater behavior, substance use generalizability of findings across age, gender, and other health- ethnicity and other factors based on design related behaviors. His characteristics). Moreover, IDA provides a means primary expertise is for testing whether key findings replicate across with latent variable multiple datasets as well as whether differences models, including exist in the strength of that replication or what multilevel linear and factors may account for lack of replication. nonlinear models, Finally, when used in secondary data analysis, IDA structural equation is a powerful tool for efficiently using resources models, latent trait to address novel questions by taking advantage of models, and latent class the rich datasets already available in the / finite mixture models. scientific community. Despite these advantages, He has published over 50 scientific papers and there are several challenges in conducting IDA. In chapters, currently serves as Associate Editor for the current workshop, we discuss the IDA Psychological Methods, and serves on the framework as well as guidelines for when IDA may editorial boards of Psychological Assessment and be an appropriate tool for a research problem Multivariate Behavioral Research. He was honored and when it may be less so. We consider core to receive an Early Career Award from the issues in planning for an IDA study including American Psychological Association in 2009 for feasibility analyses related to key issues in outstanding early-career research in the area of pooling studies with different measures and individual differences and the Raymond B. Cattell sampling frames. Because IDA is not a set of Award from the Society for Multivariate analytic techniques but an approach to Experimental Psychology in 2006 for outstanding conducting analyses through the unique early-career contributions to multivariate application of existing techniques, we present a experimental psychology. guiding framework for conducting IDA. The application of this framework is, however, Biography. Andrea idiosyncratic to the research problem at hand. To Hussong, PhD, is a exemplify this point, we provide many applied Professor of Psychology examples from our own work in examining the and the Director of the long-term longitudinal development of children Center for Developmental of alcoholic parents and matched controls pooling Science at the University across three data sets. These examples of North Carolina at demonstrate an approach to measurement Chapel Hill. The aims of harmonization using Item Response Theory and her program of research Moderated Nonlinear Confirmatory Factor are to understand early- Analysis as well as hypothesis testing using both emerging developmental multilevel and latent growth curve modeling. We pathways leading to demonstrate the use of different approaches to substance use and disorder, developmental key challenges of IDA including measurement outcomes among high-risk youth who have harmonization and inferential testing of study parents with addiction disorders, and the use of differences in hypothesized effects. Finally, we innovative methods to advance this substantive end with recommendations for planning primary research agenda. Her research focuses on data collection and analysis efforts using the IDA developmental risk processes observed in both framework as well as future directions for the short-term (e.g., observational coding and methodological development of these techniques. experience sampling designs) and long-term (i.e., multi-year longitudinal studies) passive Biography. Daniel Bauer is an Associate Professor observational designs as well as the use of of Quantitative Psychology in the L.L. Thurstone preventive interventions to understand and alter Psychometric Laboratory in the Department of these developmental risk processes. Along with Psychology at the University of North Carolina at Patrick Curran and Dan Bauer, she leads a NIDA- Chapel Hill. The aims of his program of research funded project that uses integrative data analysis are to innovate, evaluate and apply quantitative (i.e., the simultaneous analysis of multiple methods to further the study of development, independent data sets) to examine an particularly in the areas of aggression, antisocial internalizing pathway to substance use and

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disorder emerging over the first four decades of eventually psychological processes - with a life. She has served as a NIH/CSR grant review specialization in longitudinal research panelist for many years, is on the Editorial Boards methodology with John Nesselroade and Jack for journals in additions, clinical psychology and McArdle. Generally Nilam studies how short-term developmental psychology, and is a fellow in the changes (e.g., processes such as learning, APA and APS. information processing, etc.) develop over the course of the lifespan and how intraindividual change and variability study designs (e.g., (Event 3-003) Invited Workshop measurement bursts) might contribute to our Grand Salon B knowledge base. His current projects include Saturday, 8:00 am - 11:45 am examinations of: age differences in short-term dynamics at the cognitive/affective/tempera- 3-003. Growth Modeling Workshop: ment interface; cyclic patterns in the day-to-day Articulating Developmental Change with progression of emotions; and change in cognition Simple and Complex Growth Models and well-being over the lifespan, particularly in the oldest old. Methodologically, Nilam is working Instructors: Nilam Ram, Kevin J. Grimm to develop a variety of multi-person extensions of Abstract. Growth curve modeling has become a intraindividual analytic methods that maintain a mainstay in the study of development. In this focus on the individual while still tackling issues workshop we review the flexibility provided by of aggregation and generalizability. this technique for describing and testing hypotheses about intraindividual change across Biography. Kevin J. multiple occasions of measurement, and Grimm, Ph.D. interindividual differences in intraindividual (Quantitative Psychology, change. Through empirical examples we University of Virginia) is an demonstrate how simple (e.g., linear and Associate Professor in the quadratic) and complex (e.g., multiphase and Department of Psychology nonlinear) growth models can be specified using at the University of the Structural Equation Modeling and Multilevel California, Davis. He Modeling frameworks. We illustrate and discuss received his B.A. in how results are obtained and interpreted. Mathematics and Particularly, we underscore the developmental Psychology with a theory articulated and tested by each model. concentration in Education Topics covered include the inclusion of time- from Gettysburg College, and his M.A. and Ph.D. invariant and time-varying covariates, multiple in Psychology at the University of Virginia. In groups, and clustered longitudinal data. graduate school Kevin studied structural equation modeling and longitudinal data analysis (e.g., Biography. Nilam Ram, growth curve analysis, longitudinal mixture Ph.D. (Quantitative modeling, longitudinal measurement, and Psychology, University dynamic models) with Jack McArdle and John of Virginia) is an Nesselroade. He has taught at the APA workshop Assistant Professor in on Longitudinal Structural Equation Modeling the Departments of since 2004. Kevin’s research interests include Human Development & multivariate methods for the analysis of change, Family Studies and multiple group and latent class models for Psychology at understanding divergent developmental Pennsylvania State processes, and cognitive/achievement University. His current development. His current research revolves research interests have around models of nonlinear change, exploratory grown out of a history of studying change. After forms of change modeling, residual structures in obtaining his B.A. in economics, he began a job latent growth curve analysis, and the associations as a currency trader. There he studied the between early motor skills and the development movement of world markets as they jerked up, of academic skills. down and sideways. Later he moved on to the study of human movement, kinesiology, and

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(Event 3-004) Invited Workshop appeared in national magazines and an Grand Salon C anthology, as well as a chapter in a Sage book Saturday, 8:00 am - 11:45 am entitled Getting Your Book Published. She has also written five half-hour documentaries, which 3-004. Publishing Developmental Research were produced by PBS. She has taught workshops Instructor: C. Deborah Laughton on publishing for professors and graduate students at UCLA, UC Irvine, Harvard, U of IL, Abstract. Between publishing mergers and the Urbana and U of Nebraska. Web, the world of publishing has become an increasingly complex one for prospective authors. Saturday, 8:00 am - 9:45 am How can you find the right publisher for your book or journal manuscript and get the attention (Event 3-005) Paper Symposium of the editor? Taught by a leading methods Grand Salon D editor, this workshop will provide you with the Saturday, 8:00 am - 9:45 am tools to prepare a prospectus, negotiate a contract, and select the right publisher for your 3-005. Special topics in the inclusion of work. You will learn how to think about your book covariates and distal outcomes in finite or article as a publisher or journal editor would, mixture and latent class models how to sell an editor on your idea, and how to 2 get the writing finished. Using instruction, brief Chair: Eric Brown 1 exercises, and group discussion, you will be given Discussant: Elián Cabrera-Nguyen 1 2 strategies for approaching and convincing a Washington University; University of Washington publisher to publish your book, ways to make  The effects of covariates on class your article attractive to editors, and concrete enumeration for mixture models steps for finishing that half-done study on your Karen Nylund-Gibson1, Katherine Masyn2 computer. Bring your book or article idea to be 1University of California, Santa Barbara; discussed. 2Harvard University

Biography. C. Deborah Laughton, Publisher,  Covariates effects on class membership and Methodology & covariate sources of measurement non- Statistics, has over 25 invariance in mixture models Katherine Masyn1, Karen Nylund-Gibson2 years’ experience in 1 2 publishing as both an Harvard University; University of California, acquisitions editor and Santa Barbara a writer. In 2003, she joined Guilford  The consequences of latent classes: A Publications, one of simulation study of approaches to specifying the premiere and testing the effects of latent class publishers in membership on distal outcomes 1 2 psychology and education, to build a new Katherine Masyn , Karen Nylund-Gibson 1 2 program in Research Methods to cover research Harvard University; University of California design and techniques (quantitative and at Santa Barbara qualitative), evaluation, and measurement. Before joining Guilford, she built the research methods list for 15 years at Sage Publications and (Event 3-006) Paper Symposium published some of the best-selling texts, Meeting Room 12 monographs, and reference books in statistics, Saturday, 8:00 am - 9:45 am qualitative research and evaluation. She has had the privilege of creating books with such talented 3-006. Developmental Methods in Applied developmental researchers as Baltes, Shaffer, Language Research Elder, Lerner, Salkind, Jaccard, Colombo, Hardy, Chair: Jill Pentimonti Laursen, Little, and Card. In 2000, she was a The Ohio State University research investigator for the MacArthur Fellows Study that was headed by Michael Quinn Patton  Measuring Children's Development When the as the PI. Her essays and short stories have Measures Themselves Change Over Time: The

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Early Language Trajectory of Poor  A Bayesian Method for Deriving Quantitative Comprehenders Models of Individual Children’s Records Yaacov Petscher1, Laura Justice3, Tiffany Sara Baker1, Bruce Hood2, Alan Leslie3, Randy Hogan2, Andrew Mashburn4 Gallistel3 1Florida Center for Reading Research; 2The 1University of Cambridge; 2University of University of Nebraska; 3The Ohio State Bristol; 3Rutgers University University; 4The University of Virginia  Rewriting Growth Curves as Latent Profile  Differential Longitudinal Stability of Language Models and Reading Performance Eric Loken Jessica Logan, Stephen Petrill Pennsylvania State University The Ohio State University

 Teacher-Child Inferential Talk in Preschool (Event 3-008) Paper Symposium Classrooms: Sequential Relations in Small- Meeting Room 12 Group Play Saturday, 10:00 am - 11:45 am Virginia Tompkins1, Laura Justice1, Sevda Binici1, Tricia Zucker2 3-008. New Directions in Sociometric 1The Ohio State University; 2University of Classification Texas Health Science Center Chair: Antonius H. Cillessen Radboud University  Measuring Teacher Talk During Book Reading: Development and Use of a Scalable Tool Jill Pentimonti1, Tricia Zucker4, Yaacov  Determining Sociometric Status Categories Petscher3, Sonia Cabell2, Laura Justice1 Using Latent Profile Analysis 1The Ohio State University; 2The University of Marissa Smith, Julie Hubbard Virginia; 3Florida Center for Reading University of Delaware Research; 4University of Texas Health Science Center  Does Perceived Popularity Represent a Third Dimension? Incorporating Popularity into Saturday, 10:00 am - 11:45 am Traditional Sociometric Classification William Burk, Antonius Cillessen (Event 3-007) Constructed Paper Symposium Radboud University Grand Salon D Saturday, 10:00 am - 11:45 am  Identifying Subtypes of Peer Status by 3-007. Alternative Models for Analysis of Preference and Popularity: A Cross-sectional and Longitudinal Study Change and Chance Yvonne van den Berg, Antonius Cillessen Chair: James P. Selig Radboud University University of New Mexico  There’s a Chance You’re Miscalculating  Identifying Bullying Profiles Using Latent Class Modeling Chance: On the Evaluation of Chance 1 2 Performance in Developmental Research. Asha Goldweber , Tracy Evian Waasdorp , Catherine Bradshaw1 Anthony Dick, Daniel Wright 1 Florida International University Johns Hopkins Bloomberg School of Public Health; 2University of Pennsylvania

 Event/Survival Analysis: Analysis Whose Time Has Come Margaret Keiley1, Nina Martin2, Dilbur Arsiwalla1 1Auburn University; 2Vanderbilt University

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Author Index

Aber, J. Lawrence Barker, R. M. Binici, Sevda Brown, Joshua [email protected] [email protected] [email protected] [email protected] 2-009, 2-016 (83) 2-016 (5) 3-006 2-009

Akai, Carol E. Barr, Rachel F. Blair, Clancy Bukowski, William M. [email protected] [email protected] [email protected] william.bukowski@ 2-016 (71) 2-005 2-013 concordia.ca 2-016 (6), 2-016 (7), Allen, Gottfried Barrett, H Clark Blincoe, Sarai 2-016 (51) agottfried@ [email protected] [email protected] Exchange.fullerton.edu 2-006 2-016 (65) Burack, Jacob A. 1-010 [email protected] Bauer, Daniel J. Blood, Emily A. 2-016 (47) Anders, Yvonne [email protected] Emily.Blood@ yvonne.anders@ 3-002 childrens.harvard.edu Burchinal, Margaret uni-bamberg.de 2-006 [email protected] 2-016 (91) Beaumont, Jennifer L. 2-015 j-beaumont@ Blumenthal, Emily J. Anderson, Jacob E. northwestern.edu [email protected] Burfeind, Chelsea [email protected] 2-013 2-016 (57) [email protected] 2-013 2-016 (11) Beeghly, Marjorie Bornstein, Marc H. Anderson, Rawni A. [email protected] [email protected] Burk, William J. [email protected] 2-016 (33) 2-016 (27), 2-016 (58) [email protected] 2-016 (110) 3-008 Beekman, Charles Bradshaw, Catherine P. Andrews Espy, Kimberly [email protected] [email protected] Burke-Lefever, Jennifer E. [email protected] 2-016 (31) 3-008 [email protected] 1-007 2-016 (71) Belsky, Jay Branum-Martin, Lee Arim, Rubab [email protected] Lee.Branum- Buss, Kristin A. [email protected] 2-016 (52) [email protected] [email protected] 2-016 (69), 2-016 (70) 2-016 (42) 2-016 (31) Beltz, Adriene M. Arsiwalla, Dilbur [email protected] Bright, Melissa Buzhardt, Jay [email protected] 2-016 (31) [email protected] [email protected] 3-007 2-016 (76) 2-016 (110) Bergeman, Cindy S. Asher, Steven R. Cindy.S.Bergeman.1@ Brinkman, Sally Cabell, Sonia [email protected] nd.edu [email protected] [email protected] 2-016 (41) 2-016 (37) 2-010 3-006

Ba, He Bert, Shannon Brodish, Amanda B. Cabrera-Nguyen, Elián P. [email protected] [email protected] [email protected] [email protected] 2-016 (44) 2-016 (71) 2-016 (75) 3-005

Babineau, Vanessa Beyers, Jennifer M. Brophy-Herb, Holly Cairns, Ed babineau.vanessa@ [email protected] [email protected] [email protected] gmail.com 1-007 2-016 (86) 2-016 (36) 2-016 (47) Bickham, David Brown, Danielle D. Calloway, Marcia Bainter, Sierra A. david.bickham@ danielled.brown@ [email protected] [email protected] childrens.harvard.edu howard.edu 2-016 (40), 2-017 (115) 2-016 (100) 2-006 2-016 (40), 2-017 (115) Campbell, Colin Baker, Sara Bierman, Karen Brown, Eric C. colin.campbell2@ [email protected] [email protected] [email protected] mail.mcgill.ca 3-007 1-005, 1-009 1-007, 3-005 2-016 (47)

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Campbell, Cynthia Chow, Sy-Miin Cox, Ronald B. Duku, Eric [email protected] [email protected] [email protected] [email protected] 1-005 2-007 2-016 (74) 2-010

Can, Seda Cillessen, Antonius H. Cummings, E. Mark Dunn, Erin C. [email protected] [email protected] Edward.M.Cummings.10@ [email protected] 2-016 (104) 2-016 (49), 3-008 nd.edu 2-016 (56) 2-010, 2-016 (36), 2-016 Card, Noel A. Cipriano, Christina (84), 2-016 (87) Eccles, Jacquelynne S. [email protected] [email protected] [email protected] 1-008, 1-015, 2-015 2-016 (67) Dahinten, V. Susan 2-016 (75) susan.dahinten@ Carlson, Stephanie M. Clark, Caron A. nursing.ubc.ca Eidelman, Hadas [email protected] [email protected] 2-016 (70) [email protected] 2-013 1-007, 2-016 (63) 2-009 Datar, Ashlesha Carter, Alice Clark, Shaunna [email protected] Ellis-Davies, Kate [email protected] [email protected] 2-016 (73) [email protected] 2-009 2-012 2-016 (34) Davies, Patrick Castiajo, Paula Clements, Douglas patrick.davies@ Emsley, Richard [email protected] [email protected] rochester.edu richard.emsley@ 2-017 (114) 1-007 2-016 (84), 2-016 (87) manchester.ac.uk 2-016 (35) Castro-Schilo, Laura Cloney, Daniel DeLay, Dawn [email protected] [email protected] [email protected] Engle, Patrice L. 2-016 (52) 2-016 (60) 2-016 (17), 2-016 (25), [email protected] 2-016 (78) 2-016 (18) Catalano, Richard F. Coffman, Donna L. [email protected] [email protected] Dever, Bridget V. Erbacher, Monica K. 1-007 1-009 [email protected] [email protected] 2-010 2-016 (37) Caughy, Margaret Cogburn, Courtney C. margaret.caughy@ [email protected] Dick, Anthony Erickson, Lucy utsouthwestern.edu 2-016 (75) [email protected] [email protected] 2-016 (98) 3-007 2-005 Compton, Donald L. Chao, Ruth K. donald.l.compton@ Dickerson, John P. Espelage, Dorothy [email protected] vanderbilt.edu [email protected] [email protected] 2-016 (20) 1-006 2-005 2-016 (88)

Chen, Li Compton, Scott Dickson, Daniel Espy, Kimberly A. [email protected] [email protected] [email protected] [email protected] 2-016 (44) 1-009 2-016 (93) 2-013, 2-016 (63)

Cheung, Rebecca Y. M. Conejo-Bolaños, Luis D. Dickson, Daniel J. Estabrook, Ryne [email protected] luis.conejobolanos@ [email protected] [email protected] 2-010, 2-016 (87) ucr.ac.cr 2-016 (17), 2-016 (25) 1-012 2-016 (108) Chevalier, Nicolas DiCorcia, Jennifer A. Evian Waasdorp, Tracy [email protected] Connell, Arin M. jennifer.dicorcia@ [email protected] 2-013 [email protected] gmail.com 3-008 2-016 (38), 2-016 (39) 2-016 (48) Choi, Hye-Jeong Faldowski, Richard A. [email protected] Conroy, David Dirghangi, Shrija [email protected] 1-007 [email protected] [email protected] 2-016 (61) 1-012, 2-016 (90) 2-016 (17), 2-016 (25) Choi, Hye-Jeong Farr, Rachel H. [email protected] Cowan, Nelson Dong, Nianbo [email protected] 1-007, 2-016 (63) [email protected] nianbo.dong@ 2-016 (43) 2-016 (1) vanderbilt.edu 2-016 (99)

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Farran, Dale Garner, Rochelle E. Gonzalez, Amber Han, Rachel Z. [email protected] rochelle.garner@ agonzale@ [email protected] 2-016 (99) statcan.gc.ca education.ucsb.edu 2-016 (76) 2-016 (69) 1-010 Farris, Jaelyn R. Harden, K. Paige [email protected] Garnier-Villarreal, Gonzalez, Richard [email protected] 2-016 (71) Mauricio [email protected] 1-013 [email protected] 1-010 Feaster, Daniel 2-016 (108) Harder, Susanne [email protected] Goodwin, Matthew [email protected] 2-012 Gaspardo, Claudia M. [email protected] 2-016 (28) claudiagaspardo@ 1-005, 2-016 (48) Ferrer, Emilio yahoo.com.br Harding, Hilary G. [email protected] 2-016 (66) Gottfried, Adele E. [email protected] 1-005 [email protected] 2-016 (76) Gates, Kathleen 1-010 Fisher, Anna [email protected] Harding, Jessica F. [email protected] 1-005 Gottfried, Michael A. [email protected] 2-005 [email protected] 2-017 (112) Gattis, Merideth 2-016 (73) Foster, E. M. [email protected] Hardy, Sam [email protected] 2-016 (34), 2-016 (46) Green, Jonathan [email protected] 2-016 (64) jonathan.green@ 2-016 (32) Gazelle, Heidi manchester.ac.uk Fowler, Nia [email protected] 2-016 (35) Harold, Gordon T. [email protected] 2-016 (61) [email protected] 2-016 (34) Greenbaum, Paul 1-013 George, Melissa R. [email protected] Francis, David J. [email protected] 2-012 Harper, Christopher R. [email protected] 1-011, 2-016 (84) [email protected] 2-016 (42) Greenberg, Mark 2-016 (77) Gerstorf, Denis [email protected] Frankenhuis, Willem [email protected] 1-009 Harris, Katherine L. [email protected] 1-012 [email protected] 2-005 Greenwood, Charles R. 2-017 (111) Ghazarian, Sharon R. [email protected] Franzini, Luisa [email protected] 2-016 (110) Hart, Sara [email protected] 2-016 (98) [email protected] 2-016 (98) Grella, Christine 2-016 (62) Giguère, Charles-Édouard [email protected] Fricker, Damian [email protected] 2-016 (21) Hartl, Amy C. [email protected] 2-016 (22), 2-016 (68) [email protected] 2-005 Grimm, Kevin J. 2-016 (17), 2-016 (25) Goeke-Morey, Marcie C. [email protected] Fuhs, Mary [email protected] 1-012, 3-003 Hartl, Amy [email protected] 2-016 (36) [email protected] 2-016 (99) Guo, Ping 2-016 (93) Goldsmith, H. H. [email protected] Fuller-Rowell, Thomas E. [email protected] 2-016 (8) Heinzelman, Wendi tom.fullerrowell@ 2-016 (89) wendi.heinzelman@ gmail.com Haas, Sarah rochester.edu 2-016 (75) Goldweber, Asha [email protected] 2-016 (44) [email protected] 2-016 (50) Gallistel, Randy 3-008 Helm, Jonathan L. [email protected] Hafen, Christopher A. [email protected] 3-007 Golonka, Megan [email protected] 2-016 (52) [email protected] 2-016 (78) Garber, Judy 2-016 (53) Henderson, Craig [email protected] Hall, Elizabeth [email protected] 2-016 (59) Gommans, Rob [email protected] 2-012 [email protected] 2-016 (21) 2-016 (49)

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Henrich, Christopher Hollenstein, Tom Janus, Magdalena Kelcey, Ben [email protected] tom.hollenstein@ [email protected] [email protected] 2-016 (77) queensu.ca 2-010 1-006 2-016 (33) Henry, Kimberly L. Jia, Rongfang Keller, Peggy [email protected] Hood, Bruce jia.31@ [email protected] 2-011, 2-012 [email protected] buckeyemail.osu.edu 2-016 (65) 3-007 2-016 (26) Herbers, Janette Kimonis, Eva R. [email protected] House, Bailey Johansson, Boo [email protected] 2-016 (19) [email protected] [email protected] 2-011 2-005 2-016 (97) Herrenkohl, Todd I. Kirkham, Natasha [email protected] Howard, Waylon J. Johnson, Craig natasha.kirkham@ 1-007 [email protected] [email protected] gmail.com 2-016 (110) 2-013 2-005 Hiatt, Cody [email protected] Hox, Joop Johnson, Janice Kirkorian, Heather L. 2-016 (17), 2-016 (25), 2- [email protected] [email protected] [email protected] 016 (93) 2-016 (104) 2-016 (3) 2-006

Higgins-D'Alessandro, Ann Hubbard, Julie A. Johnson, Scott Kiuru, Noona [email protected] [email protected] [email protected] [email protected] 2-016 (8) 3-008 2-005 2-016 (10)

Hilbrink, Elma Hughes, Diane Jones, Stephanie M. Klein, Vivian C. [email protected] [email protected] stephanie_m_jones@ [email protected] 2-016 (34) 2-016 (20), 2-017 (112) gse.harvard.edu 2-016 (2) 2-009 Hill, Nancy E. Hughes-Scalise, Abigail Klostermann, Susan [email protected] [email protected] Jose, Paul E. [email protected] 2-016 (20) 2-016 (38), 2-016 (39) [email protected] 2-016 (38), 2-016 (39) 2-002 Hipwell, Alison E. Hussong, Andrea Knight, George P. [email protected] [email protected] Jozsa, Krisztian [email protected] 2-016 (95) 3-002 [email protected] 2-016 (92) 2-016 (106) Hofer, Scott M. Huth-Bocks, Alissa C. Koeppe, Simo [email protected] [email protected] Justice, Laura [email protected] 2-010, 2-016 (16), 2-017 (111) [email protected] 2-016 (28) 2-016 (97) 3-006 Hutton, R. S. Kohen, Dafna E. Hofer, Scott [email protected] Kamp Dush, Claire [email protected] [email protected] 2-007 [email protected] 2-016 (69) 2-016 (105) 2-016 (26) Ialongo, Nicholas Koss, Kalsea J. Hoffman, Lesa [email protected] Kamphaus, Randy W. [email protected] [email protected] 1-010 [email protected] 2-016 (36), 2-016 (84), 2-016 (16) 2-010 2-016 (87) Ignjatovic, Zeljko Hogan, Tiffany [email protected] Kanatsu, Akira Kotila, Letitia tiffany.hoganunl@ 2-016 (44) [email protected] [email protected] gmail.com 2-016 (20) 2-016 (26) 3-006 Jagenow, Danilo danilo.jagenow@ Kappler, Gregor Kouros, Chrystyna D. Holland, Adam fu-berlin.de [email protected] [email protected] [email protected] 2-016 (6), 2-016 (51) 2-016 (4) 2-016 (59) 2-016 (11) Jaki, Thomas Keiley, Margaret K. Kuhl, Anthony P. [email protected] [email protected] [email protected] 1-011 3-007 1-012

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Kurtz, Tanja Li, Yan Lu, Zhenqiu McArdle, John J. tanja.kurtz@ [email protected] [email protected] [email protected] geronto.uni-erlangen.de 2-010 2-007 1-008 2-016 (109) Linebarger, Deborah L. Malanchuk, Oksana McCoach, Betsy Lach, Lucyna M. deborah- [email protected] [email protected] [email protected] [email protected] 2-016 (75) 1-006 2-016 (69) 2-006 Malone, Patrick S. McCormick, Carolyn Lamont, Andrea E. Linhares, Maria Beatriz M. [email protected] [email protected] [email protected] [email protected] 2-012, 2-016 (12) 2-016 (45) 2-016 (12) 2-016 (2), 2-016 (66) Mandell, Dorothy J. McCullough, Courtney Larzelere, Robert E. Lippold, Melissa [email protected] [email protected] robert.larzelere@ [email protected] 2-016 (57) 2-016 (76) okstate.edu 1-009 2-016 (74) Marcus, Jade V. McCune, Luke A. Lipsey, Mark [email protected] [email protected] Laughton, C. Deborah mark.w.lipsey@ 2-016 (64) 2-016 (110) CDeborah.Laughton@ vanderbilt.edu guilford.com 2-016 (99) Marion, Donna McDonald, Kristina L. 3-004 [email protected] [email protected] Little, Michelle 2-016 (10) 2-016 (41) Laursen, Brett [email protected] [email protected] 2-016 (29) Martin, Nina C. McFarlan, Chastity C. 2-016 (10), 2-016 (17), [email protected] chastity.mcfarlan@ 2-016 (25), 2-016 (78), Little, Todd D. 3-007 bison.howard.edu 2-016 (93) [email protected] 2-016 (40), 2-017 (115) 1-015, 2-008, 2-015, Martinez, Francisco E. Le, Huynh-Nhu 2-016 (88) [email protected] Mehta, Paras [email protected] 2-016 (66) [email protected] 2-016 (20) Liu, Siwei 2-016 (42) [email protected] Martins, Carla Lemery-Chalfant, Kathryn 1-005 [email protected] Merrilees, Christine E. [email protected] 2-017 (114) [email protected] 1-013, 2-016 (89) Lo, Lawrence L. 2-016 (36), 2-016 (84) [email protected] Martins, Eva C. Leslie, Alan 2-007, 2-016 (94) [email protected] Meyers, Joel [email protected] 2-017 (114) [email protected] 3-007 Loeber, Rolf 2-016 (77) [email protected] Martoccio, Tiffany Leve, Leslie D. 2-016 (95) [email protected] Miller, Portia [email protected] 2-016 (86) [email protected] 1-013 Logan, Jessica 2-016 (103) [email protected] Mashburn, Andrew Lewin-Bizan, Selva 1-006 [email protected] Molano, Andres [email protected] 3-006 [email protected] 2-016 (80) Logan, Jessica 2-009 [email protected] Maslowsky, Julie Li, Libo 3-006 [email protected] Molenaar, Peter [email protected] 2-016 (85) [email protected] 2-016 (21) Loken, Eric 1-005, 1-012, 2-007, [email protected] Masten, Ann 2-016 (31), 2-016 (94) Li, Runze 1-010, 3-007 [email protected] [email protected] 2-016 (19) Morgan, George A. 2-016 (90) Losardo, Diane George.Morgan@ [email protected] Masyn, Katherine E. Colostate.edu Li, Tan 2-007 [email protected] 2-016 (106) [email protected] 1-002, 1-010, 2-012, 2-016 1-011 Loughran, Thomas A. (12), 2-016 (56), 3-005 Morris, Pamela [email protected] [email protected] 2-011 2-016 (83)

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Moulson, Margaret O'Connell, Ann Petras, Hanno Rao, Mrinalini A. mmoulson@ [email protected] hpetras@ [email protected] psych.ryerson.ca 1-006 jbsinternational.com 2-016 (88) 2-016 (24) 1-002, 1-011, 2-012 Oh, WonJung Rao, Nirmala Muniz, Graciela [email protected] Petrill, Stephen [email protected] graciela.muniz@ 1-010 [email protected] 2-016 (18) mrc-bsu.cam.ac.uk 3-006 2-016 (97) Olino, Thomas M. Rast, Philippe [email protected] Petscher, Yaacov [email protected] Musci, Rashelle J. 2-016 (95) [email protected] 2-010 [email protected] 1-006, 2-016 (101), 3-006 1-010 Olson, Brent F. Raufelder, Diana [email protected] Piccinin, Andrea M. diana.raufelder@ Narayan, Angela 2-016 (70) [email protected] fu-berlin.de [email protected] 2-016 (16), 2-016 (97) 2-016 (6), 2-016 (7), 2-016 (19) Opfer, John 2-016 (51) [email protected] Pilon, Mathieu Narde, Ane 2-016 (23) mathieu.pilon@ Raver, C Cybele ane.narde@ umontreal.ca [email protected] atferdssenteret.no Osório, Ana 2-016 (22) 2-013, 2-016 (54), 2-016 (82) [email protected] 2-016 (72) 2-017 (114) Pincus, Aaron Natsuaki, Misaki N. [email protected] Reid, Joan A. [email protected] Pap-Szigeti, Robert 1-012, 2-016 (90) [email protected] 1-013 pap-szigeti.robert@ 2-016 (81) gamf.kefo.hu Plowman, Elizabeth Neiderhiser, Jenae M. 2-016 (106) [email protected] Reiss, David [email protected] 2-016 (19) [email protected] 1-013 Papp, Lauren M. 1-013 [email protected] Pluess, Michael Nelson, Jennifer M. 2-016 (59) [email protected] Rhee, Soo [email protected] 2-016 (52) [email protected] 1-007, 2-013 Parent, Sophie 1-013 sophie.parent@ Powers, Christopher J. Nesselroade, John R. umontreal.ca [email protected] Rhemtulla, Mijke [email protected] 2-016 (22) 1-009 [email protected] 1-015 1-004 Pascual-Leone, Juan Price, Larry R. Neuharth-Pritchett, Stacey [email protected] [email protected] Rhoades, Kimberly A. [email protected] 2-016 (3) 1-010 [email protected] 2-016 (55) 1-013 Patterson, Charlotte J. Puder, Justin Nicholson, Jody S. [email protected] [email protected] Rich, Michael [email protected] 2-016 (43) 2-016 (25), 2-016 (93) michael.rich@ 2-016 (71) childrens.harvard.edu Peck, Steve C. Putnick, Diane L. 2-006 Nurmi, Jari-Erik [email protected] [email protected] [email protected] 2-016 (75) 2-016 (27), 2-016 (58) Richler, Jennifer 2-016 (10) [email protected] Peckins, Melissa Quinn, Patrick D. 2-013 Nylund-Gibson, Karen [email protected] [email protected] knylund@ 2-016 (96) 1-013 Richmond, Ashley D. education.ucsb.edu [email protected] 1-010, 2-012, 3-005 Pena, Juan Raines, Tara C. 2-016 (17), 2-016 (25) [email protected] [email protected] O'Brien, T. C. 2-012 2-010 Rishikof, Stephanie [email protected] stephanie.rishikof@ 2-016 (89) Pentimonti, Jill M. Ram, Nilam mail.mcgill.ca [email protected] [email protected] 2-016 (47) 1-006, 3-006 1-005, 1-012, 2-007, 2-016 (90), 3-003

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Ritchie, Kathy Schatschneider, Shirlow, Peter Stockwell, Timothy [email protected] Christopher [email protected] [email protected] 2-017 (113) [email protected] 2-016 (36) 2-016 (15) 1-006, 2-016 (62) Robitaille, Annie Shiyko, Mariya Sturge-Apple, Melissa annie.g.robitaille@ Schmid, Lorrie A. [email protected] melissa.sturge-apple@ gmail.com [email protected] 2-016 (90) rochester.edu 2-016 (97) 2-016 (53) 2-016 (44) Shrier, Lydia A. Rocha, Luciana C. Schmidt, Karen M. Lydia.Shrier@ Sugden, Nicole [email protected] [email protected] childrens.harvard.edu [email protected] 2-016 (2) 2-016 (37) 2-006 2-016 (24)

Roche, Kathleen M. Schoppe-Sullivan, Sarah Smith, Linda B. Sullivan, Christopher J. [email protected] sschoppe-sullivan@ [email protected] [email protected] 2-016 (98) ehe.osu.edu 2-005 2-011, 2-016 (81) 2-016 (26) Rogers, Sally Smith, Marissa A. Sumaroka, Mariya sally.rogers@ Schulenberg, John marissa.anne.smith@ masha.sumaroka@ ucdmc.ucdavis.edu [email protected] gmail.com gmail.com 2-016 (45) 2-016 (85) 3-008 2-016 (58)

Roosa, Mark W. Schwerdtfeger, Kami Snidman, Nancy Sun, Jin [email protected] kami.schwerdtfeger@ [email protected] [email protected] 2-016 (92) okstate.edu 2-016 (48) 2-016 (18) 2-016 (74) Rossbach, Hans-Guenther Soares, Isabel Susman, Elizabeth J. hans-guenther.rossbach@ Selig, James P. [email protected] [email protected] uni-bamberg.de [email protected] 2-017 (114) 2-016 (96) 2-016 (91) 1-003, 3-007 South, Susan C. Suwalsky, Joan T. Rovine, Michael J. Setodji, Claude M. [email protected] [email protected] [email protected] [email protected] 1-013 2-016 (58) 1-005, 2-007, 2-016 (94) 2-016 (103) Spangler Avant, Tamara Swan, Kristen Roy, Amanda L. Sevcik, Rose A. [email protected] [email protected] [email protected] [email protected] 2-016 (61) 2-005 2-016 (54) 2-016 (5) Sparks, Catharine Sylva, Kathy Rush, Jonathan Shaffer, Anne [email protected] kathy.sylva@ [email protected] [email protected] 2-016 (16), 2-016 (105) education.ox.ac.uk 2-016 (105) 2-016 (76) 2-016 (91) Spitler, Mary Elaine Sakkalou, Elena Shapka, Jennifer D. [email protected] Séguin, Jean R. [email protected] [email protected] 1-007 [email protected] 2-016 (34) 2-016 (70) 2-016 (22), 2-016 (68) Sravish, Akhila V. Salmela-Aro, Katariina Shaw, Daniel S. [email protected] Tayler, Collette katariina.salmela- [email protected] 2-016 (33) collette.tayler@ [email protected] 1-013 unimelb.edu.au 2-016 (10) Stallings, Michael C. 2-016 (60) Sheffield, Tiffany D. michael.stallings@ Sammons, Pamela [email protected] colorado.edu Taylor, Jeanette pamela.sammons@ 2-013 2-016 (52) [email protected] education.ox.ac.uk 2-016 (62) 2-016 (91) Sheffield, Tiffany D. Steele, Joel tsheffield2@ [email protected] Taylor, Laura K. Sarama, Julie unlnotes.unl.edu 1-005 [email protected] [email protected] 1-007, 2-016 (63) 2-016 (36), 2-016 (84) 1-007 Stepp, Stephanie D. [email protected] 2-016 (95)

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Tein, Jenn-Yun Ursache, Alexandra Waschbusch, Daniel Wu, Rachel [email protected] [email protected] [email protected] [email protected] 2-016 (92) 2-016 (54) 2-016 (50) 2-005

Thiessen, Erik Vaever, Mette Way, Niobe Wu, Wei [email protected] [email protected] [email protected] [email protected] 2-005 2-016 (28), 2-016 (30) 2-017 (112) 1-004 Yang, Na Thompson, Celine Valeri, Beatriz O. Webb, Mi-young L. [email protected] [email protected] [email protected] [email protected] 1-011 2-016 (102) 2-016 (66) 2-016 (55) Yoo, Yeonsoo Thompson, Kara D. van de Schoot, Rens Weeks, Molly S. [email protected] [email protected] [email protected] [email protected] 2-016 (79) 2-016 (15) 2-004, 2-016 (104) 2-016 (41) Young, Christopher J. [email protected] Thornberry, Terrence P. van den Berg, Yvonne H. Weinert, Sabine 2-016 (23) [email protected] [email protected] sabine.weinert@uni- 2-011 3-008 bamberg.de Young, Gregory 2-016 (91) gregorys.young@ Thorpe, Karen Van Horn, M. Lee ucdmc.ucdavis.edu Weintraub, Sandra [email protected] [email protected] 2-016 (45) 2-016 (60) 1-007, 1-011, 2-012 sweintraub@ Yu, Chen northwestern.edu [email protected] Tompkins, Virginia Varjas, Kristen 2-013 2-005 [email protected] [email protected] White, Rebecca M. state.edu 2-016 (77) [email protected] Yu, Tianyi 3-006 2-016 (92) [email protected] Vazquez, Karinna 1-010 Torrente, Catalina [email protected] Whitesell, Nancy R. [email protected] 2-016 (93) nancy.whitesell@ucdenver. Zachrisson, Henrik D. 2-009 edu [email protected] Veenstra, René 2-016 (20) 2-016 (82) Toumbourou, John W. [email protected] Widaman, Keith F. Zeiders, Katharine H. john.toumbourou@ 2-003 [email protected] katherine.zeiders@ deakin.edu.au 1-012, 2-008, 2-016 (52) gmail.com 1-007 Veríssimo, Manuela 2-016 (92) [email protected] Wiebe, Sandra A. Tremblay, Richard E. 2-017 (114) [email protected] Zelazo, Philip D. richard.ernest.tremblay@ 2-013 [email protected] umontreal.ca Volling, Brenda 2-013, 2-016 (22) Winstanley, Alice 2-016 (22) [email protected] [email protected] Zhai, Fuhua 1-010 2-016 (46) [email protected] Tronick, Ed 2-016 (72) Ed.Tronick@ Votruba-Drzal, Elizabeth Witkiewitz, Katie childrens.harvard.edu [email protected] [email protected] Zhang, Zhiyong 2-016 (33) 2-016 (103) 2-012 [email protected] 1-012, 2-007 Tucker-Drob, Elliot M. Walker, Dale Wolf, Sharon Zhou, Yan [email protected] [email protected] [email protected] [email protected] 1-013 2-016 (110) 2-016 (83) 2-016 (8) Wolfe, Christopher Turner, Kimberly Wallner-Allen, Kathleen [email protected] Zimprich, Daniel kimberly.turner@ [email protected] 1-007 daniel.zimprich@ vanderbilt.edu 2-013 geronto.uni-erlangen.de 2-016 (99) Wright, Daniel B. 2-016 (109) Wang, Wei [email protected] Uhl, George [email protected] 3-007 Zucker, Tricia [email protected] 2-012 [email protected] Wright, Michelle 3-006 1-010 [email protected] 2-016 (13), 2-016 (14)

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