When measuring latent constructs, for example, language ability, we use statistical models to specify appropriate relationships between the latent construct and observe responses to test items. These models rely on theoretical assumptions to ensure accurate parameter estimates for valid inferences based on the test results. This dissertation…

We address the problem of selecting the best of a set of units based on a criterion variable, when its value is recorded for every unit subject to estimation, measurement, or another source of error. The solution is constructed in a decision-theoretical framework, incorporating the consequences (ramifications) of the various kinds of error that…

An empirical evidence for independent samples of a population regarding measurement invariance implies that factor structure of a measurement tool is equal across these samples; in other words, it measures the intended psychological trait within the same structure. In this case, the evidence of construct validity would be strengthened within the…

The unique conceptual framework and language of generalizability theory are presented. While this chapter is relevant to any area in which generalizability theory is applicable, it emphasizes evaluation research, and most examples come from that area. (Author/PN)

Most training programs in education and psychology focus on classical test theory techniques for assessing score dependability. This paper discusses generalizability theory and explores its concepts using a small heuristic data set. Generalizability theory subsumes and extends classical test score theory. It is able to estimate the magnitude of…

A latent trait model, the Rasch, was fitted to a criterion-referenced test. Approximately 90 percent of the items fit the model. Those items which fit the model were then calibrated. Based on the item calibration, individual ability estimates and the standard errors of those estimates were calculated. Using the ability estimates, it was possible,…

If a loss function is available specifying the social cost of an error of measurement in the score on a unidimensional test, an asymptotic method, based on item response theory, is developed for optimal test design for a specified target population of examinees. Since in the real world such loss functions are not available, it is more useful to…