Computing confidence intervals around generalizability coefficients has long been a challenging task in generalizability theory. This is a serious practical problem because generalizability coefficients are often computed from designs where some facets have small sample sizes, and researchers have little guide regarding the trustworthiness of the…

This study utilizes an analysis of diminishing returns to examine the relationship between sample size and item parameter estimation precision when utilizing the Masters' Partial Credit Model for polytomous items. Item data from the standardization of the Batelle Developmental Inventory, 3rd Edition were used. Each item was scored with a…

In generalizability theory studies in large-scale testing contexts, sometimes a facet is very sparsely crossed with the object of measurement. For example, when assessments are scored by human raters, it may not be practical to have every rater score all students. Sometimes the scoring is systematically designed such that the raters are…

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

Contemporary educational accountability systems, including state-level systems prescribed under No Child Left Behind as well as those envisioned under the "Race to the Top" comprehensive assessment competition, rely on school-level summaries of student test scores. The precision of these score summaries is almost always evaluated using models that…

Generalizability theory is used to examine the impact of scaling gradients on a single-item Direct Behavior Rating (DBR). A DBR refers to a type of rating scale used to efficiently record target behavior(s) following an observation occasion. Variance components associated with scale gradients are estimated using a random effects design for persons…

Estimating standard errors of estimated variance components has long been a challenging task in generalizability theory. Researchers have speculated about the potential applicability of the bootstrap for obtaining such estimates, but they have identified problems (especially bias) in using the bootstrap. Using Brennan's bias-correcting procedures…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

The extent to which a scale score generalizes to a latent variable common to all of the scale's indicators is indexed by the scale's general factor saturation. Seven techniques for estimating this parameter--omega[hierarchical] (omega[subscript h])--are compared in a series of simulated data sets. Primary comparisons were based on 160 artificial…