LEADER 03803nam 2200661Ia 450 001 9910813079503321 005 20200520144314.0 010 $a1-136-76111-X 010 $a1-136-76112-8 010 $a0-203-82196-3 024 7 $a10.4324/9780203821961 035 $a(CKB)2670000000163919 035 $a(EBL)692401 035 $a(OCoLC)764572379 035 $a(SSID)ssj0000641548 035 $a(PQKBManifestationID)11432573 035 $a(PQKBTitleCode)TC0000641548 035 $a(PQKBWorkID)10628217 035 $a(PQKB)10473263 035 $a(MiAaPQ)EBC692401 035 $a(Au-PeEL)EBL692401 035 $a(CaPaEBR)ebr10551303 035 $a(CaONFJC)MIL760903 035 $a(OCoLC)794489446 035 $a(EXLCZ)992670000000163919 100 $a20101104d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical approaches to measurement invariance /$fRoger E. Millsap 205 $a1st ed. 210 $aNew York $cRoutledge$dc2011 215 $a1 online resource (359 p.) 300 $aDescription based upon print version of record. 311 $a1-84872-819-0 311 $a1-84872-818-2 320 $aIncludes bibliographical references and indexes. 327 $aFront 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; Estimation 327 $aFit 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 Example 327 $a9. Bias In Measurement and PredictionPredictive Bias; Prediction Within the Factor Analysis Model; General Latent Variable Models; Conclusion; References; Author Index; Subject Index 330 $aThis 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, 606 $aPsychological tests 606 $aPsychology$xStatistical methods 606 $aPsychometrics 615 0$aPsychological tests. 615 0$aPsychology$xStatistical methods. 615 0$aPsychometrics. 676 $a150.28/7 700 $aMillsap$b Roger Ellis$01710752 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910813079503321 996 $aStatistical approaches to measurement invariance$94101608 997 $aUNINA