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El. knyga: Assessing Measurement Invariance for Applied Research

(University of Massachusetts, Amherst)

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"Assessing Measurement Invariance for Applied Research will provide psychometricians and researchers across diverse disciplines in the social sciences the necessary knowledge and skills to select and apply appropriate methods to assess measurement invariance. It is a user-friendly guide that describes a variety of statistical methods using a pedagogical framework emphasizing conceptual understanding with extensive illustrations that demonstrate how to use software to analyze real data. A companion website (people.umass.edu/cswells) provides downloadable computer syntax and the data sets demonstrated in this book so readers can use them to become familiar with the analyses and understand how to apply the methods with proficiency to their own work. Evidence-supported methods that can be readily applied to real world data are described and illustrated, providing researchers with many options from which to select given the characteristics of their data. The approaches include observed-score methods and thosethat use item response theory models and confirmatory factor analysis,"--

Recenzijos

'Measurement invariance has become a key concept in social sciences. Craig S. Well's book offers a comprehensive overview of MI approaches as well as practical examples, which will allow the reader to carry out measurement invariance studies in different contexts.' Paula Elosua Oliden, Professor of Psychometrics, University of the Basque Country, Spain 'The text provides a concise and clear treatment of the numerous approaches used to assess measurement invariance. With practitioners in mind, the examples with computer syntax and output support your ability to conduct and correctly interpret these analyses. Practitioners and students will benefit from reading this book.' Sara J. Finney, Professor of Graduate Psychology and Associate Director of the Center for Assessment and Research Studies, James Madison University, USA 'This volume in the International Test Commission series is a hands-on book for applied researchers. It does a good job in instructing readers to detect and interpret measurement invariance, an important topic in developing measures that are fair and appropriate for all.' Kurt F. Geisinger, W.C. Meierhenry Distinguished University Professor of Educational Psychology and Director of the Buros Center for Testing, University of Nebraska-Lincoln, USA 'This book is clear, well structured, practice-oriented, and grounded on theory and methodology. It will be a great help for students and researchers in the social sciences, education, and health sciences. The complementary website is also very useful for applying the techniques presented in the book. In short, it is a must-read.' José Muńiz, Professor of Psychometrics, University of Nebrija, Spain 'This is a comprehensive pedagogical guide to assessing measurement invariance and has wide appeal to researchers, practitioners, and graduate students. The book reads as if written by a seasoned teacher and I especially appreciate the data sets and computer software syntax, which allow you to practice the methods described.' Jennifer Randall, Associate Dean for Academic Affairs and Director of Evaluation for the Center for Educational Assessment, University of Massachusetts Amherst, USA 'The author certainly delivers on the promise of its title in providing comprehensive, yet accessible, guidance to those tasked with evaluating invariance in practice. It presents cogent and succinct descriptions of advanced measurement concepts, connecting the theory of these ideas to practical applications using numerous examples and data files.' April. L. Zenisky, Research Associate Professor of Educational Assessment, University of Massachusetts Amherst, USA

Daugiau informacijos

This user-friendly guide illustrates how to assess measurement invariance using computer programs, statistical methods, and real data.
List of Figures ix
List of Tables xii
Preface xix
1 Introduction 1(16)
What Is Measurement Invariance?
1(4)
Why Should We Assess Measurement Invariance?
5(3)
Forms of DIF
8(2)
Classification of DIF Detection Methods
10(1)
The Conditioning Variable: To Purify or Not to Purify?
11(2)
Considerations When Applying Statistical Tests for DIF
13(4)
2 Observed-Score Methods 17(91)
Transformed Item Difficulty (Delta-Plot) Method
19(12)
Mantel-Haenszel DIF Procedure
31(21)
Standardization DIF Procedure
52(13)
Logistic Regression
65(21)
SIBTEST
86(18)
Applying Observed-Score Methods to Incomplete Data Sets
104(4)
3 Item Response Theory 108(53)
Unidimensional IRT Models
111(1)
Dichotomous Item Responses
112(8)
Polytomous Item Responses
120(7)
Multidimensional IRT Models
127(2)
Model Assumptions
129(7)
Parameter Estimation
136(5)
The Latent Variable Scale
141(2)
Linking IRT Scales
143(3)
Item and Testing Information Functions
146(3)
Test Information
149(3)
IRT Parameter Estimation Software
152(9)
4 Methods Based on Item Response Theory 161(84)
b- and a-Plots
166(11)
Lord's Chi-Square and Wald Statistic
177(21)
Likelihood-Ratio Test
198(15)
Raju's Area DIF Measures
213(9)
DFIT
222(21)
Applying IRT DIF Methods to Incomplete Data Sets
243(2)
5 Confirmatory Factor Analysis 245(50)
Basic Principles of CFA
246(24)
Example of CFA Using Mplus
270(11)
Analyzing Categorical Indicators
281(7)
Description and Example of the Bifactor Model
288(7)
6 Methods Based on Confirmatory Factor Analysis 295(74)
Multigroup Confirmatory Factor Analysis
296(36)
MIMIC Model
332(35)
Applying CFA-Based Methods to Incomplete Data Sets
367(2)
Appendix A: A Brief R Tutorial 369(7)
References 376(12)
Author Index 388(3)
Subject Index 391
Craig S. Wells is a professor in the Research, Educational Measurement, and Psychometrics Program at the University of Massachusetts Amherst, where he teaches courses on statistics and psychometrics. He co-edited Educational Measurement: From Foundations to Future (2016) and was President of the Northeastern Educational Research Association in 2017.