03786oam 2200649I 450 991081307950332120230725032942.01-136-76111-X1-136-76112-80-203-82196-310.4324/9780203821961 (CKB)2670000000163919(EBL)692401(OCoLC)764572379(SSID)ssj0000641548(PQKBManifestationID)11432573(PQKBTitleCode)TC0000641548(PQKBWorkID)10628217(PQKB)10473263(MiAaPQ)EBC692401(Au-PeEL)EBL692401(CaPaEBR)ebr10551303(CaONFJC)MIL760903(OCoLC)794489446(EXLCZ)99267000000016391920180706d2011 uy 0engur|n|---|||||txtccrStatistical approaches to measurement invariance /Roger E. MillsapNew York :Routledge,2011.1 online resource (359 p.)Description based upon print version of record.1-84872-819-0 1-84872-818-2 Includes bibliographical references and indexes.Front Cover; Statistical Approaches to Measurement Invariance; Copyright Page; Contents; Preface; Acknowledgments; 1. Introduction; What Is Measurement Invariance?; Is Measurement Bias an Important Problem?; About This Book; 2. Latent Variable Models; General Features; Model Restrictions; Problems in Latent Variable Models; 3. Measurement Bias; Multiple Populations; Measurement Invariance; Dimensionality and Invariance; Conditioning on Observed Scores; Appendix; 4. The Factor Model and Factorial Invariance; The Common Factor Model in Multiple Populations; Identification; EstimationFit EvaluationInvariance Constraints; An Example; Appendix: Factorial Invariance and Selection; 5. Factor Analysis in Discrete Data; The Factor Model; Estimation; Tests of Invariance; An Example; 6. Item Response Theory: Models, Estimation, Fit Evaluation; Models; Estimation; Model Fit Evaluation; 7. Item Response Theory: Tests of Invariance; Forms of Bias; Likelihood-Ratio Tests; Wald Statistics; Parameter Linkage; Effect Size Measures; The DFIT Approach; An Example; 8. Observed Variable Methods; Dichotomous Item Methods; Polytomous Item Methods; Random Effects Models; SIBTEST; An Example9. Bias In Measurement and PredictionPredictive Bias; Prediction Within the Factor Analysis Model; General Latent Variable Models; Conclusion; References; Author Index; Subject IndexThis book reviews the statistical procedures used to detect measurement bias. Measurement bias is examined from a general latent variable perspective so as to accommodate different forms of testing in a variety of contexts including cognitive or clinical variables, attitudes, personality dimensions, or emotional states. Measurement models that underlie psychometric practice are described, including their strengths and limitations. Practical strategies and examples for dealing with bias detection are provided throughout.The book begins with an introduction to the general topic,Psychological testsPsychologyStatistical methodsPsychometricsPsychological tests.PsychologyStatistical methods.Psychometrics.150.28/7Millsap Roger Ellis.1710752MiAaPQMiAaPQMiAaPQBOOK9910813079503321Statistical approaches to measurement invariance4101608UNINA