One of the major theoretical and practical developments in testing is latent trait analysis and item response theory. This report provides a guide for practitioners in understanding, evaluating, and using these developments to meet their testing needs. (Author)

Multivariate generalizability techniques are used to bridge the gap between psychometric constraints and the tables of specifications needed in test development. Techniques are illustrated with results from the American College Testing Assessment Program. (Author/PN)

A general framework for conducting generalizability analyses is presented. Generalizability theory is extended to situations in which the objects of measurement are not persons but other factors, such as instructional objectives, stages of learning, and treatments. (Author/PN)

This chapter presents several facets of a new approach that uses generalizability theory to conduct cross-level inference in psychological and educational research. Unlike past models for cross-level research, this approach facilitates multiple-level investigations to test the external validity of results and findings. (Author/PN)

Latent trait models provide a new scale for reporting educational and psychological measurements. Characteristics, interpretations, and uses of these scales are considered. (Author/RL)

While some forms of test bias (for example, bias in selection and prediction) appear amenable to definitional consensus, a definition of cultural bias will remain problematic so long as it is confused with the nature/nurture issue. (Author/BW)

California Assessment Program's application of matrix sampling and item response curve theory to the scaling and reporting of state assessment data is described. It is designed to express educational outcomes in an efficient and interpretable form that is both immediately informative and suited to analysis over extended periods of time.…