Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…

Though calibration of an achievement test within psychological and educational context is very often carried out by the Rasch model, data sampling is hardly designed according to statistical foundations. However, Kubinger, Rasch, and Yanagida (2009) recently suggested an approach for the determination of sample size according to a given Type I and…

Whenever one uses a composite scale score from item responses, one is tacitly assuming that the scale is dominantly unidimensional. Investigating the unidimensionality of item response data is an essential component of construct validity. Yet, there is no universally accepted technique or set of rules to determine the number of factors to retain…

Whether item response theory (IRT) is useful to the small-scale testing practitioner is examined. The stability of IRT item parameters is evaluated with respect to the classical item parameters (i.e., p-values, biserials) obtained from the same data set. Previous research investigating the effect of sample size on IRT parameter estimation has…

A scoring algorithm for performance assessments is described that is based on expert judgments but requires the rating of only a sample of performances. A regression-based policy capturing procedure was implemented for clinicians evaluating skills of 280 medical students. Results demonstrate the usefulness of the algorithm. (SLD)