DOCSLIB.ORG

Convergent and Divergent Validity of the Learning Transfer Questionnaire. Annette Irving Bookter Louisiana State University and Agricultural & Mechanical College

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Convergent and Divergent Validity of the Learning Transfer Questionnaire. Annette Irving Bookter Louisiana State University and Agricultural & Mechanical College Louisiana State University LSU Digital Commons LSU Historical Dissertations and Theses Graduate School 1999 Convergent and Divergent Validity of the Learning Transfer Questionnaire. Annette Irving Bookter Louisiana State University and Agricultural & Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Recommended Citation Bookter, Annette Irving, "Convergent and Divergent Validity of the Learning Transfer Questionnaire." (1999). LSU Historical Dissertations and Theses. 7068. https://digitalcommons.lsu.edu/gradschool_disstheses/7068 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Historical Dissertations and Theses by an authorized administrator of LSU Digital Commons. For more information, please contact [email protected]. INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of com puter printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note wiH indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6” x 9” black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. Bell & Howell Information and Learning 300 North Zeeb Road. Ann Arbor, Ml 48106-1346 USA UMI*800-521-0600 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CONVERGENT AND DIVERGENT VALIDITY OF THE LEARNING TRANSFER QUESTIONNAIRE A Dissertation Submitted to the Graduate Faculty o f the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The School of Vocational Education by Annette Irving Bookter B.S., Southern University, 1970 M.S., The American University, 1990 December 1999 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. UMI Number 9960039 UMI* UMI Microform9960039 Copyright 2000 by Bell & Howell Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. Bell & Howell Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, Ml 48106-1346 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ACKNOWLEDGEMENTS My thanks go to my Heavenly Father and my earthly family, without whom this would have not been possible. A special thanks to my mom and dad for always being there for me, and who always taught us that belief in God and education were keys to success. Thanks to my faculty committee for believing in me. Special thanks to Dr. Elwood F. Holton, HI, Faculty Committee Chair, for the opportunity to be involved in this cutting edge learning transfer research. I would like to thank Fredrick C. Spathel£ Human Resources Director, Mid-west Region, United States Postal Service, for folly supporting this study. Lastly, I would like to thank the Center for Creative Leadership, Greensboro, North Carolina, for contributing components of the KEYS instrument for utilization in this study. ii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE OF CONTENTS ACKNOWLEDGMENTS.................................................................................. ii LIST OF TABLES.............................................................................................. v UST OF FIGURES.......................................................................................... ix ABSTRACT....................................................................................................... x CHAPTER 1 INTRODUCTION....................................................................... I Background of the Study ....................................................... 2 A Statement of the Problem ..................................................... 7 Purpose of the Study ................................................................ 8 Research Questions .................................................................. 8 Key Terms................................................................................ 9 2 LITERATURE REVIEW............................................................. 10 Overview: Transfer o f Training ............................................... 10 Validation: A Conceptual Framework..................................... 28 Convergent and Divergent Validity ........................................ 30 Strategies for Construct Validity Studies .............................. 31 Background and Development of the LTQ ............................ 33 3 METHODOLOGY................................. 43 Procedures: Research Question One ....................................... 43 Procedures for Selection of Comparison Instruments ............ 44 Procedures: Research Question Two ...................................... 48 4 RESULTS OF RESEARCH QUESTION ONE......................... 59 Measures Used in this Study ................................................. 62 Items Used in the LTQ Sub-scales and Comparison Measures ...................................................... 97 5 RESULTS OF RESEARCH QUESTION TWO........................ 121 Summary o f Data Analysis ................................................ 124 6 DISCUSSION AND CONCLUSIONS..................................... 143 Summary o f Procedures ...................................................... 143 Discussion of Findings ....................................................... 145 Conclusions ........................................................................ 163 Limitations of This Study ................................................... 173 Recommendations for Future Research ............................... 174 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. REFERENCES............................................................................................. 178 APPENDIXES A TRAINING TRANSFER ENVIRONMENT INSTRUMENT..................................................................... 190 B LEARNING TRANSFER QUESTIONNAIRE - VERSION 2........ 200 C INSTRUCTIONS FOR PARTICIPANTS.............................. 210 D OTHER MEASURES INVESTIGATED FOR THE STUDY............................................. 213 E PEARSON’S CORRELATION MATRIX............................. 218 F LTQ INTER-SCALE CORRELATION MATRIX................ 238 G PEARSON’S PARTIAL CORRELATION MATRIX 243 H PERMISSION LETTERS...................................................... 254 VITA............................................................................................................... 263 iv Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. LIST OF TABLES 1. Dimensions of Situational Cues and Consequences Used in Rouiller and Goldstein (1993) Transfer Climate Model .................... 35 2. LTQ Factors: Holton, Bates, Ruona & Leimbach (1998) ...................... 40 3. Criteria and Steps Utilized in Identifying Comparison Measures For this Study .................................................................................... 44 4. Selected General Rating Criteria for Evaluating Measure ...................... 47 5. Sample by District, Number of Participants, Number of Hours of Training, Title of Training and Title of Participants ...................................................................................... 49 6. Positive and Negative Affect Schedule Descriptors ............................... 53 7. Identification of the Instruments Used in This Study in the General Rating Criteria ................................................................... 60 8. Work Environment Scale Dimensions, Sub-scales and Definitions ............................................................................................ 62 9. Job Descriptive Index Sub-scales and Definitions ............................... 65 10. KEYS Environmental Scale Dimensions and Definitions ........................ 68 11. Perceived Work Environment Sub-scales and Definitions ................... 71 12. Index o f Organizational Reaction Sub-scales and Definitions ................ 75 13. Leader Reward Behavior Sub-scales and Definitions ............................ 77 14. Facet Specific Job Satisfaction and Definitions ..................................... 79 15. Work Related Expectancies Sub-scale
Load more

Recommended publications
  • “Is the Test Valid?” Criterion-Related Validity– 3 Classic Types Criterion-Related Validity– 3 Classic Types
    “Is the test valid?” Criterion-related Validity – 3 classic types • a “criterion” is the actual value you’d like to have but can’t… Jum Nunnally (one of the founders of modern psychometrics) • it hasn’t happened yet and you can’t wait until it does claimed this was “silly question”! The point wasn’t that tests shouldn’t be “valid” but that a test’s validity must be assessed • it’s happening now, but you can’t measure it “like you want” relative to… • It happened in the past and you didn’t measure it then • does test correlate with “criterion”? -- has three major types • the specific construct(s) it is intended to measure Measure the Predictive Administer test Criterion • the population for which it is intended (e.g., age, level) Validity • the application for which it is intended (e.g., for classifying Concurrent Measure the Criterion folks into categories vs. assigning them Validity Administer test quantitative values) Postdictive Measure the So, the real question is, “Is this test a valid measure of this Administer test Validity Criterion construct for this population for this application?” That question can be answered! Past Present Future The advantage of criterion-related validity is that it is a relatively Criterion-related Validity – 3 classic types simple statistically based type of validity! • does test correlate with “criterion”? -- has three major types • If the test has the desired correlation with the criterion, then • predictive -- test taken now predicts criterion assessed later you have sufficient evidence for criterion-related
    [Show full text]
  • Validity and Reliability in Social Science Research
    Education Research and Perspectives, Vol.38, No.1 Validity and Reliability in Social Science Research Ellen A. Drost California State University, Los Angeles Concepts of reliability and validity in social science research are introduced and major methods to assess reliability and validity reviewed with examples from the literature. The thrust of the paper is to provide novice researchers with an understanding of the general problem of validity in social science research and to acquaint them with approaches to developing strong support for the validity of their research. Introduction An important part of social science research is the quantification of human behaviour — that is, using measurement instruments to observe human behaviour. The measurement of human behaviour belongs to the widely accepted positivist view, or empirical- analytic approach, to discern reality (Smallbone & Quinton, 2004). Because most behavioural research takes place within this paradigm, measurement instruments must be valid and reliable. The objective of this paper is to provide insight into these two important concepts, and to introduce the major methods to assess validity and reliability as they relate to behavioural research. The paper has been written for the novice researcher in the social sciences. It presents a broad overview taken from traditional literature, not a critical account of the general problem of validity of research information. The paper is organised as follows. The first section presents what reliability of measurement means and the techniques most frequently used to estimate reliability. Three important questions researchers frequently ask about reliability are discussed: (1) what Address for correspondence: Dr. Ellen Drost, Department of Management, College of Business and Economics, California State University, Los Angeles, 5151 State University Drive, Los Angeles, CA 90032.
    [Show full text]
  • Validity of the Patient Health Questionnaire-9 in Assessing Depression Following Traumatic Brain Injury
    J Head Trauma Rehabil Vol. 20, No. 6, pp. 501–511 c 2005 Lippincott Williams & Wilkins, Inc. Validity of the Patient Health Questionnaire-9 in Assessing Depression Following Traumatic Brain Injury Jesse R. Fann, MD, MPH; Charles H. Bombardier, PhD; Sureyya Dikmen, PhD; Peter Esselman, MD; Catherine A. Warms, PhD; Erika Pelzer, BS; Holly Rau, BS; Nancy Temkin, PhD Objective: To test the validity and reliability of the Patient Health Questionnaire-9 (PHQ-9) for diag- nosing major depressive disorder (MDD) among persons with traumatic brain injury (TBI). Design: Prospective cohort study. Setting: Level I trauma center. Participants: 135 adults within 1 year of complicated mild, moderate, or severe TBI. Main Outcome Measures: PHQ-9 Depression Scale, Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (SCID). Results: Using a screening criterion of at least 5 PHQ-9 symptoms present at least several days over the last 2 weeks (with one being depressed mood or anhedonia) maximizes sensitivity (0.93) and specificity (0.89) while providing a positive predictive value of 0.63 and a negative predictive value of 0.99 when compared to SCID diagnosis of MDD. Pearson’s correlation between the PHQ-9 scores and other depression measures was 0.90 with the Hopkins Symptom Checklist depression subscale and 0.78 with the Hamilton Rating Scale for Depression. Test-retest reliability of the PHQ-9 was r = 0.76 and κ = 0.46 when using the optimal screening method. Conclusions: The PHQ-9 is a valid and reliable screening tool for detecting MDD in persons with TBI.
    [Show full text]
  • Reliability and Validity of the Measurement--Two Concepts Which We Will Discuss Further Later in This Lab
    INTRODUCTION Sociologist James A. Quinn states that the tasks of scientific method are related directly or indirectly to the study of similarities of various kinds of objects or events. One of the tasks of scientific method is that of classifying objects or events into categories and of describing the similar characteristics of members of each type. A second task is that of comparing variations in two or more characteristics of the members of a category. Indeed, it is the discovery, formulation, and testing of generalizations about the relations among selected variables that constitute the central task of scientific method. Fundamental to the performance of these tasks is a system of measurement. S.S. Stevens defines measurement as "the assignment of numerals to objects or events according to rules." This definition incorporates a number of important distinctions. It implies that if rules can be set up, it is theoretically possible to measure anything. Further, measurement is only as good as the rules that direct its application. The "goodness" of the rules reflects on the reliability and validity of the measurement--two concepts which we will discuss further later in this lab. Another aspect of definition given by Stevens is the use of the term numeral rather than number. A numeral is a symbol and has no quantitative meaning unless the researcher supplies it through the use of rules. The researcher sets up the criteria by which objects or events are distinguished from one another and also the weights, if any, which are to be assigned to these distinctions. This results in a scale.
    [Show full text]
  • Convergent and Discriminant Validity with Formative Measurement: a Mediator Perspective Xuequn Wang Murdoch University, Perth, AUS, [email protected]
    Journal of Modern Applied Statistical Methods Volume 14 | Issue 1 Article 11 5-1-2015 Convergent and Discriminant Validity with Formative Measurement: A Mediator Perspective Xuequn Wang Murdoch University, Perth, AUS, [email protected] Brian F. French Washington State University, [email protected] Paul F. Clay Fort Lewis College, [email protected] Follow this and additional works at: http://digitalcommons.wayne.edu/jmasm Recommended Citation Wang, Xuequn; French, Brian F.; and Clay, Paul F. (2015) "Convergent and Discriminant Validity with Formative Measurement: A Mediator Perspective," Journal of Modern Applied Statistical Methods: Vol. 14 : Iss. 1 , Article 11. DOI: 10.22237/jmasm/1430453400 Available at: http://digitalcommons.wayne.edu/jmasm/vol14/iss1/11 This Regular Article is brought to you for free and open access by the Open Access Journals at DigitalCommons@WayneState. It has been accepted for inclusion in Journal of Modern Applied Statistical Methods by an authorized editor of DigitalCommons@WayneState. Journal of Modern Applied Statistical Methods Copyright © 2015 JMASM, Inc. May 2015, Vol. 14, No. 1, 83-106. ISSN 1538 − 9472 Convergent and Discriminant Validity with Formative Measurement: A Mediator Perspective Xuequn Wang Brian F. French Paul F. Clay Murdoch University Washington State University Fort Lewis College Perth, Australia Pullman, WA Durango, CO The ability to validate formative measurement has increased in importance as it is used to develop and test theoretical models. A method is proposed to gather convergent and discriminant validity evidence of formative measurement. Survey data is used to test the proposed method. Keywords: Causal indicators, formative measurement, construct validity, convergent validity, discriminant validity, mediator Introduction There has been a vigorous debate and discussion about the issues surrounding the application of formative measurement (Bollen, 2007; Howell et al., 2007a, 2007b; Petter et al., 2007) and how to validate this specific kind of measurement model (Hardin et al.
    [Show full text]
  • Assessing Convergent and Discriminant Validity of the Motivation Construct for the Technology Integration Education (TIE) Model
    Assessing Convergent and Discriminant Validity of the Motivation Construct for the Technology Integration Education (TIE) Model Kevin A. Engellant University of Montana Western Denise D. Holland University of Montana Western Randy T. Piper Motivation researchers have given high priority to the nomological validity of the motivation construct by creating diverse models such as the technology integration education (TIE) model as part of the technological, pedagogical, and content knowledge (TPACK) research agenda. However, researchers have not given equally high priority to convergent validity and discriminant validity. This study incorporated the multitrait-multimethod (MTMM) matrix to discover evidence of convergent validity and discriminant validity for self-determination theory motivation and social cognitive theory motivation. The researchers found limited evidence of convergent validity and discriminant validity for the motivation construct. INTRODUCTION Motivation is perennially important because it has diverse implications for academic research in education, psychology, business, and public administration (Greene, 2005; Perry & Hondeghem, 2008; Rainey, 2014) and real-world applications for teachers, parents, coaches, and others (Ryan & Deci, 2000a, 2000b). Motivation is among the most studied constructs in the social sciences. In industrial and organizational psychology, along with job satisfaction (Cranny, Smith, & Stone, 1992; Locke, 1969; Spector, 1992, 1987, 1997), motivation may be the most studied construct (Latham, 2012; Pinder, 2008). In educational psychology, along with self-efficacy (Bandura, 1977a, 1977b, 1997, 2009; Bandura & Locke, 2003; Gist & Mitchell, 1992), motivation may be the most studied construct (Brophy, 2010; Schunk, Pintrich, & Meece, 2008; Stipek, 2002; Weiner, 1972, 1980, 1986, 1990). Education motivation textbooks have identified expectancy value, attribution, social cognitive, goal- setting, and self-determination theory as leading theories (Brophy, 2010; Schunk et al., 2008; Stipek, 2002).
    [Show full text]
  • Construct Validation 1 Construct Validation in Organizational
    Construct Validation 1 Construct Validation in Organizational Behavior Research Jeffrey R. Edwards University of North Carolina The author thanks Richard P. DeShon, Fritz Drasgow, and Larry J. Williams for their helpful comments on an earlier version of this chapter. In J. Greenberg (Ed.), Organizational behavior: The state of the science (2nd ed., pp. 327-371). Mahwah, NJ: Erlbaum, 2003. Construct Validation 2 A theory comprises two sets of relationships, one that links constructs that constitute the substance of the theory, and another that maps constructs onto phenomena that can be directly observed and measured (Bagozzi & Phillips, 1982; Costner, 1969). In organizational behavior (OB) research, theory development emphasizes relationships among constructs but devotes relatively little attention to relationships between constructs and measures (Schwab, 1980). These latter relationships are crucial to theory development, because they provide the means by which constructs become accessible to empirical research and theories are rendered testable. Moreover, because the relationships between constructs and measures are integral to a theory, theory testing is incomplete unless these relationships are scrutinized. Thus, the relationships between constructs and measures constitute an auxiliary theory that itself is subject to empirical testing and falsification (Costner, 1969; Cronbach & Meehl, 1955; Schwab, 1980). Relationships between constructs and measures are the essence of construct validity. At its most fundamental level, construct validity concerns the degree to which a measure captures its intended theoretical construct (Cronbach & Meehl, 1955). Although the notion of construct validity is straightforward, procedures used to assess construct validity are complex and have evolved considerably during the past several decades. These procedures present a potentially bewildering array of choices for OB researchers confronted with crucial task of establishing the correspondence between theoretical constructs and their measures.
    [Show full text]
  • Quantifying Construct Validity: Two Simple Measures
    Quantifying Construct Validity: Two Simple Measures The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Westen, Drew, and Robert Rosenthal. 2003. Quantifying construct validity: Two simple measures. Journal of Personality and Social Psychology 84, no. 3: 608-618. Published Version http://dx.doi.org/10.1037/0022-3514.84.3.608 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:3708469 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Journal of Personality and Social Psychology Copyright 2003 by the American Psychological Association, Inc. 2003, Vol. 84, No. 3, 608–618 0022-3514/03/$12.00 DOI: 10.1037/0022-3514.84.3.608 Quantifying Construct Validity: Two Simple Measures Drew Westen Robert Rosenthal Emory University University of California, Riverside and Harvard University Construct validity is one of the most central concepts in psychology. Researchers generally establish the construct validity of a measure by correlating it with a number of other measures and arguing from the pattern of correlations that the measure is associated with these variables in theoretically predictable ways. This article presents 2 simple metrics for quantifying construct validity that provide effect size estimates indicating the extent to which the observed pattern of correlations in a convergent-discriminant validity matrix matches the theoretically predicted pattern of correlations. Both measures, based on contrast analysis, provide simple estimates of validity that can be compared across studies, constructs, and measures meta-analytically, and can be implemented without the use of complex statistical proce- dures that may limit their accessibility.
    [Show full text]
  • Constructing Indices and Scales
    Constructing Indices and Scales Hsueh-Sheng Wu CFDR Workshop Series June 8, 2015 1 Outline • What are scales and indices? • Graphical presentation of relations between items and constructs for scales and indices • Why do sociologists need scales and indices? • Similarities and differences between scales and indices • Constructions of scales and indices • Criteria for evaluating a composite measure • Evaluation of scales and indices • How to obtain the sum score of a scale or an index? • Conclusion 2 What Are Scales and Indices? • Scales and indices are composite measures that use multiple items to collect information about a construct. These items are then used to rank individuals. • Examples of scales: – Depression scales – Anxiety scale – Mastery scale • Examples of indices: – Socio-Economic Status (SES) index – Consumer price index – Stock market index – Body mass Index 3 Graphical Presentation of Relations between Items and Constructs for Scales and Indices • Scale: Feeling sad e Depression Sleepless e Suicidal Ideation e • Index: Education Social Income Economic e Status Occupation 4 Why Do Sociologists Need Scales and Indices? • Most social phenomenon of interest are multi- dimensional constructs and cannot be measured by a single question, for example: – Well-being – Violence • When a single question is used, the information may not be very reliable because people may have different responses to a particular word or idea in the question. • The variation of one question may not be enough to differentiate individuals. • Scales and indices allow researchers to focus on large theoretical constructs rather than individual empirical indicator. 5 Similarities and Differences between Scales and Indices Similarities: • Both try to measure a composite construct or constructs.
    [Show full text]
  • Convergent and Discriminant Validity of the Test of Sensitivity
    University of Montana ScholarWorks at University of Montana Graduate Student Theses, Dissertations, & Professional Papers Graduate School 1975 Convergent and discriminant validity of the test of sensitivity Marianne Thomas Spitzform The University of Montana Follow this and additional works at: https://scholarworks.umt.edu/etd Let us know how access to this document benefits ou.y Recommended Citation Spitzform, Marianne Thomas, "Convergent and discriminant validity of the test of sensitivity" (1975). Graduate Student Theses, Dissertations, & Professional Papers. 5607. https://scholarworks.umt.edu/etd/5607 This Thesis is brought to you for free and open access by the Graduate School at ScholarWorks at University of Montana. It has been accepted for inclusion in Graduate Student Theses, Dissertations, & Professional Papers by an authorized administrator of ScholarWorks at University of Montana. For more information, please contact [email protected]. CONVERGENT AND DISCRIMINANT VALIDITY OF THE TEST OF SENSITIVITY By Marianne Spitzform B.S. Allegheny College, 1968 M.T.S. Harvard Divinity School, 1970 Presented in partial fulfillment of the requirements for the degree of Master of Arts UNIVERSITY OF MONTANA 1975 Approved by; , Board of Examiners Deaia'L/Gradu UMI Number: EP41071 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Dissertation Publishing UMI EP41071 Published by ProQuest LLC (2014). Copyright in the Dissertation held by the Author.
    [Show full text]
  • The Validity of Measurement Methods, Text Version
    University of York Department of Health Sciences Measuring Health and Disease The validity of measurement methods Validity In this lecture I shall discuss some of the statistical procedures used in the validation of measurement techniques. There is no universally accepted definition of validity, but we shall regard a measurement technique as valid if it measures what we want it to measure. Because of the great variety of measurement techniques, there is no strategy of validation which can be used in all cases. Validation is very much an ad hoc process. For example, if we want to validate a new sphygmomanometer we can compare readings directly with those made with a random zero instrument, which we regard as a valid method. If there is good agreement between the two instruments, we can conclude that the new instrument is valid. However, if we want to validate a set of respiratory symptom questions used in the study of possible effects on children of air pollution or passive smoking, we cannot compare the answers to these questions with any objective measurement of respiratory distress. We must rely on more indirect methods to assess validity, such as the relationship between answers to similar questions asked to children and their parents, or between answers and measured lung function. Because of the great variety of measures for which we seek to investigate the validity, there are many terms used. Some of these do not have consistent interpretations and may overlap. They include concurrent validity, construct validity, content validity, convergent validity, criterion validity, discriminant validity, divergent validity, face validity, and predictive validity.
    [Show full text]
  • The Construct Validity of the Clinical Assessment of Working Memory Ability
    Louisiana State University LSU Digital Commons LSU Doctoral Dissertations Graduate School 2008 The construct validity of the clinical assessment of working memory ability Benjamin David Hill Louisiana State University and Agricultural and Mechanical College, [email protected] Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_dissertations Part of the Psychology Commons Recommended Citation Hill, Benjamin David, "The onc struct validity of the clinical assessment of working memory ability" (2008). LSU Doctoral Dissertations. 1637. https://digitalcommons.lsu.edu/gradschool_dissertations/1637 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Doctoral Dissertations by an authorized graduate school editor of LSU Digital Commons. For more information, please [email protected]. THE CONSTRUCT VALIDITY OF THE CLINICAL ASSESSMENT OF WORKING MEMORY ABILITY A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College In partial fulfillment of the Requirements for the degree of Doctor of Philosophy In The Department of Psychology by Benjamin David Hill B.S., Coastal Carolina University, 1999 M.A., Wake Forest University, 2003 August 2008 Acknowledgements I would like to thank the large number of individuals who have aided me with the completion of this project. In particular, I would like to single out Dr. Drew Gouvier, Dr. Emily Elliott, Jill Shelton, Russ Pella, and Matt Calamia for helping me with the design, implementation, and/or collection of data for this dissertation. I would also like to thank my dissertation committee for providing many helpful suggestions that resulted in an improved final work.
    [Show full text]