Module 28: Raju’s Differential Functioning of Items and Tests

Product not yet rated

Nambury S. Raju (1937–2005) developed two model-based indices for differential item functioning(DIF) during his prolific career in psychometrics. Both methods, Raju’s area measures (Raju, 1988) and Raju’s DFIT (Raju, van der Linden, & Fleer, 1995), are based on quantifying the gap between item characteristic functions (ICFs). This approach provides an intuitive and flexible methodologyfor assessing DIF. The purpose of this tutorial is to explain DFIT and show how this methodology can be utilized in a variety of DIF applications.

Keywords: differential item functioning, DIF, differential test functioning, DTF, item response theory, IRT, measurement equivalence, Raju

Chris Oshima

Professor, Georgia State University

Chris Oshima is a full professor in the Department of Educational Policy Studies at Georgia State University. She graduated from the University of Florida in 1989 with a Ph.D. in foundations of education specializing in research and evaluation design, testing and measurement and data analysis methods. During her tenure at Georgia State University she has taught numerous courses in quantitative methods and measurement, including Quantitative Methods and Analysis I, II, III, Educational Measurement, Introduction to Item Response Theory and Advanced Item Response Theory. Her primary research interests are in educational measurement and statistics, especially in the area of item response theory (IRT) and differential item functioning (DIF).

Scott Morris

Professor of Psychology, Lewis College of Human Sciences, Illinois Institute of Technology

Scott Morris received a Ph.D. in Industrial-Organizational Psychology in 1994 from the University of Akron. He earned a B.A. in Psychology from the University of Northern Iowa in 1987. He is a fellow the Society for Industrial and Organizational Psychology, and serves on the editorial boards of Journal of Applied Psychology, Organizational Research Methods, Journal of Business and Psychology, and International Journal of Testing.

Morris teaches courses in personnel selection, covering topics such as job analysis, test development and validation, and legal issues. He also teaches courses in basic and multivariate statistics and multilevel data analysis.

Morris is actively involved in research on applied statistics and personnel selection. Much of his work involves the development of statistical methods. This includes methods of meta-analysis for program evaluation research, statistics for assessing adverse impact in employee selection systems, and applications of advanced psychometric models (e.g., computer adaptive testing). He also conducts research exploring issues of validity and discrimination in employee selection systems.