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15 International Total Survey Error Conference TSE15 2015 International Total Survey Error Conference TSE15 Improving Data Quality in the Era of Big Data Final Program September 20–22, 2015 Short Courses – September 19, 2015 Renaissance Baltimore Harborplace Hotel Baltimore, Maryland, USA www.tse15.org [email protected] Follow us on @totalsurveyerr #TSE15 2 Welcome to the TSE15 Welcome to the 2015 International Total Survey Error Conference. TSE15 TSE15 is designed for statisticians, survey managers and methodologists, pollsters, public opinion researchers, and marketing research professionals focused on survey quality and the challenges of big data. The Total Survey Error concept summarizes the ways a survey estimate may deviate from the corresponding value in the population. Conference Organizing Committee Dr. Stephanie Eckman (co-chair) Senior Researcher, Institute for Employment Research (IAB) Brad Edwards (co-chair) Vice President and Deputy Area Director, Westat Dr. Paul Biemer Distinguished Fellow, RTI International Dr. Frauke Kreuter Associate Professor, Joint Program in Survey Methodology, University of Maryland Dr. Edith de Leeuw Professor, Utrecht University Dr. Lars Lyberg Professor, Department of Statistics, University of Stockholm Dr. Clyde Tucker Principal Survey Methodologist, American Institutes for Research Dr. Brady West Research Assistant Professor, Survey Methodology Program, Survey Research Center, Institute for Social Research, University of Michigan-Ann Arbor TSE15 Supporters TSE15 is supported by the Council of Professional Associations on Federal Statistics (COPAFS), with conference support from Kellen (formerly The Sherwood Group Inc.) Improving Data Quality www.tse15.org TSE15 in the Era of Big Data #TSE15 3 Thank You to our Sponsors Event Sponsors AMERICAN ASSOCIATION FOR PUBLIC OPINION RESEARCH Government Statistics Section of ASA Social Statistics Section of ASA Survey Research Methods Section of ASA Contributors Diamond Level Gold Level Survey Research Center, University Of Michigan Conference Supporters Partners COPAFS (Council of Professional Associations on Federal Statistics) www.tse15.org Improving Data Quality #TSE15 in the Era of Big Data TSE15 4 Conference Schedule Saturday, September 19 Sunday, September 20 9:00 a.m. – 5:00 p.m. 9:30 – 11:30 a.m. Short Courses Paper Session I Total Survey Error Framework: Essentials Interactions of Survey Error and Ethnicity I Room: Homeland, 5th Floor Room: Maryland A, 5th Floor Paul Biemer, Distinguished Fellow, Session Chair: Sunghee Lee RTI International, University of North Carolina, Chapel Hill; Lars Lyberg, Professor Emeritus, University of Stockholm Ethnic Minorities in Surveys: Invited Presentation Applying the TSE Paradigm to Total Survey Error in Project Management Surveys Among Ethnic Minority Groups to Assess the Room: Federal Hill, 5th Floor Relationship Between Survey Design, Sample Frame and Survey Data Quality Brad Edwards, Vice President, Director of Field Services and Deputy Director, Westat; Joost Kappelhof Institute for Social Research/SCP Michelle Amsbary, Senior Study Director and Project Director, How Does Language Shape Public Opinion? American National Election Survey at Westat, Maryland Efren Perez Vanderbilt University A Small Course on Big Data for Survey Researchers Survey Error Associated with the Translation of U.S. Room: Maryland A, 5th Floor Education Level Categories into Spanish Trent Buskirk, Vice President of Statistics and Patricia Goerman, Leticia Fernandez, Kathleen Kephart Methodology, Marketing Systems Group; U.S. Census Bureau Frauke Kreuter, Professor at the Joint Program in Survey The Role of Time Perspectives on Subjective Methodology and Professor of Statistics and Social Probability Response Patterns Among Hispanics Science Research at the University of Mannheim Sunghee Lee University of Michigan Sexual Orientation and Behavior Item Nonresponse and Measure Concordance Across Race/Ethnicity, Sex, Interview Language, and English Proficiency: Evidence from Five Cycles of the California Health Interview Survey Matt Jans1, David Grant2, Joseph Viana2 1Center for Health Policy Research, 2UCLA Center for Health Policy Research Improving Data Quality www.tse15.org TSE15 in the Era of Big Data #TSE15 5 Conference Schedule Interviewer Effects Across Error Sources Nonresponse Room: Maryland E, 5th Floor Room: Homeland, 5th Floor Session Chair: Stephanie Eckman Session Chair: Lin Wang Interviewers’ Attitudes Towards Surveys, Interviewer Identification and Reduction of Nonresponse Bias in Experience, Response Locus of Control, Personality Address-Based Sample Surveys and the Impact on Cooperation with CATI-Surveys Burton Levine Volker Huefken RTI International Heinrich-Heine-Universität Düsseldorf How to Estimate the Nonresponse Error in Probability Mode Effect in Voting Behavior and Social Trust: Terms A Comparison Between CAPI and CATI Daniel Thorburn Pei-shan Liao Dept. of Statistics, Stockholm University Academia Sinica An Imputation Approach to Handling Nonignorable Influence of Prior Respondent-Interviewer Interaction Nonresponse Using Paradata on Disclosure in Audio Computer-assisted Self- Seho Park1, Jae Kwang Kim1, Kimin Kim2 interviewing (ACASI) 1Iowa State University, 2Korea Labor Institute Hanyu Sun Westat A Forest Full of Respondents: Comparing Logistic Regression and Random Forest Models for Response Propensity Weighting Adjustments Trent Buskirk1, Stanislav Kolenikov2 1Marketing Systems Group, 2Abt SRBI The Intersection of Sampling and Nonresponse: Does Repeated Sampling of Some Individuals Affect Nonresponse Bias? Jennifer Sinibaldi1, Anton Örn Karlsson2 1JPSM, University of Maryland, 2Statistics Iceland Comparison Between Substitution and Strata Collapsing for Sampling Variance Estimation Under the Presence of Nonresponding PSUs Raphael Nishimura, James Lepkoswki University of Michigan www.tse15.org Improving Data Quality #TSE15 in the Era of Big Data TSE15 6 Conference Schedule Sunday, September 20 Methods for Assessing and Integrating 9:30 – 11:30 a.m. Solutions for Total Survey Error in a Large Paper Session I (continued) National Survey: The National Crime Data Falsification: Who, Why and How to Victimization Survey Detect It Room: Guilford, 5th Floor Room: Maryland D/F, 5th Floor Session Chair: Marcus Berzofsky Session Chair: Nancy Bates The Impact of Adaptive Design on Nonresponse Bias and Precision Taking Fabrication Detection and Prevention Beyond Michael Planty, Lynn Langton the Interviewer Level U.S. Bureau of Justice Statistics Steve Koczela The MassINC Polling Group Methods for Reducing TSE in Subnational Estimates: An Assessment of Coverage Error Through the Curb Stoning and Culture Comparison of Nationally Calibrated Weights to Arthur Kennickell Subnational Area-specific Calibrated Weights Federal Reserve Board Bonnie Shook-Sa1, Marcus Berzofsky1, G. Lance Couzens1, Andrew Moore1, Philip Lee1, Lynn Langton2, Data Falsification: Who, Why and How to Detect It Michael Planty2 Cathy Furlong 1RTI International, 2U.S.Bureau of Justice Statistics Integrity Management Services, LLC Discussion on Reducing Total Survey Error in the Understanding Core Reasons Why Falsification Occurs National Crime Victimization Survey During Field Data Collection Lynn Langton Timothy Olson U.S. Bureau of Justice Statistics U.S. Census Bureau Comparing Error Structures for Estimates of Rape Detecting Data Falsification in Survey Research and Sexual Assault: The Design of the National Survey Noble Kuriakose1, Michael Robbins2 on Health and Safety 1 2 SurveyMonkey, Princeton University David Cantor1, Shannan Catalano2, Allen Beck2 1Westat, 2U.S. Bureau of Justice Statistics Minimizing Total Survey Error in the National Crime Victimization Survey: An Assessment of Methods to Adjust for Recall Bias and Fatigue Andrew Moore, Marcus Berzofsky, Lance Couzens, Dave Heller, Chelsea Burfeind RTI International Improving Data Quality www.tse15.org TSE15 in the Era of Big Data #TSE15 7 Conference Schedule Coverage Error in Practice: Record Linkage Operational Issues for Measuring Frame Room: Gibson, 6th Floor Coverage of Demographic Surveys Session Chair: Frauke Kreuter Room: Federal Hill, 5th Floor Errors in Linking Survey and Invited Presentation Session Chair: Cha-Chi Fan Administrative Data Is the Whole Sampling Frame Less than the Sum of Its Joe Sakshaug Parts? How Operational Weaknesses Can Undermine University of Manchester Frame Coverage The Nature of the Bias when Studying Only Linkable Clifford Loudermilk Person Records: Evidence from the American U.S. Census Bureau Community Survey Assessing Lister Error Associated with Frame Adela Luque1, Amy O’Hara1, David Brown1, Brittany Bond2 Creation — Comparing Address Listing Results and 1U.S. Census Bureau, 2U.S. Department of Commerce 2010 Census Outcomes Determining Recall Errors in Retrospective Life Aliza Kwiat Course Data – An Approach Using Linked Survey and U.S. Census Bureau Administrative Data Selection of Predictors to Model Coverage Errors in Stefanie Unger, Britta Matthes the Master Address File Institute for Employment Research Andrew Raim Statistical Analysis of Files Created Through Record U.S. Census Bureau Linkage: Joint Modeling of Linkage and Analysis Michael Larsen A Sensitivity Analysis of Coverage Error for The George Washington University Demographic Surveys Cha-Chi Fan Use of Linked Survey Data to Develop Responsive U.S. Census Bureau Design Sampling Strategies in the Medical Expenditure Panel Survey Lisa Mirel, Sadeq Chowdhury, Steven Machlin DHHS\AHRQ Analytic Error as an Important Invited Presentation
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