Generalizability theory is a modern and powerful framework for conducting reliability analyses. It is flexible to accommodate both random and fixed facets. However, there has been a relative scarcity in the practical literature on how to handle the fixed facet case. This article aims to provide practitioners a conceptual understanding and…

Although generalizability theory (GT) designs typically are analyzed using analysis of variance (ANOVA) procedures, they also can be integrated into structural equation models (SEMs). In this tutorial, we review basic concepts for conducting univariate and multivariate GT analyses and demonstrate advantages of doing such analyses within SEM…

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 present paper suggests that multivariate techniques are very important in social science research, and that canonical correlation analysis may be particularly useful. The logic of canonical analysis is explained and discussed. The necessity of using replicability/generalizability analyses is argued. It is suggested that cross-validation…

The main purpose of this study is to examine the content structure of the Multistate Bar Examination (MBE) using the "table of specifications" model from the perspective of multivariate generalizability theory. Specifically, using MBE data collected over different years (six administrations: three from the February test and three from July test),…