This 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.

Roger E. Millsap is a Professor in the Department of Psychology and a faculty member in the Doctoral Program in Quantitative Psychology at Arizona State University. He received his Ph.D. in Psychology in 1983 from the University of California-Berkeley. Dr. Millsap's research interests include psychometrics, latent variable models, and multivariate statistics. He has published more than 60 papers in professional journals and co-edited the Sage Handbook of Quantitative Methods in Psychology with Alberto Maydeu-Olivares in 2009. Dr. Millsap is a Past-President of the Psychometric Society, of Division 5 of the American Psychological Association, and of the Society of Multivariate Experimental Psychology. He is a Past -Editor of Multivariate Behavioral Research and is the current Executive Editor of Psychometrika.

1. Introduction. 2. Latent Variable Models. 3. Measurement Bias. 4. The Factor Model and Factorial Invariance. 5. Factor Analysis in Discrete Data. 6. Item Response Theory: Models, Estimation, Fit Evaluation. 7. Item Response Theory: Tests of Invariance. 8. Observed Variable Methods. 9. Bias in Measurement and Prediction.