Researchers often use generalizability theory to estimate relative error variance and reliability in teaching observation measures. They also use it to plan future studies and design the best possible measurement procedures. However, designing the best possible measurement procedure comes at a cost, and researchers must stay within their budget…

There are situations within middle school settings where measurements of students and teachers are used for high-stakes decisions. For example, student performance is used as an indicator of teacher quality or determines student eligibility for particular types of support services. Given the high-stakes nature of these types of assessments,…

Standard-setting methods are widely used to determine cut scores on a test that examinees must meet for a certain performance standard. Because standard setting is a measurement procedure, it is important to evaluate variability of cut scores resulting from the standard-setting process. Generalizability theory is used in this study to estimate…

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 zeitgeist for reform in education precipitated a number of changes in assessment. Among these are performance assessments, sometimes linked to "high stakes" accountability decisions. In some instances, the trustworthiness of these decisions is based on variance components and error variances derived through generalizability theory.…

Four approaches to estimating interrater reliability in early childhood special education research are illustrated and compared: correlation, comparison of means, percentage of agreement, and generalizability theory techniques. Generalizability theory techniques are proposed as a method for estimating the amount of variance attributable to…

A methodology is presented for minimizing mean error variance in generalizability studies when resource constraints are imposed. The optimal number of observations and conditions of facets for random model, fully crossed one- and two-facet designs can be decided. Parallel closed form formulas can be determined for other designs. (SLD)

The framework and procedures of generalizability theory are introduced and illustrated in this instructional module that uses a hypothetical scenario involving writing proficiency. Generalizability analyses are useful for understanding the relative importance of various sources of error and for designing efficient measurement procedures. (SLD)

A measurement approach called generalizability theory (G-theory) is an important alternative to the more familiar classical measurement theory that yields less useful coefficients such as alpha or the KR-20 coefficient. G-theory is a theory about the dependability of behavioral measurements that allows the simultaneous estimation of multiple…

Generalizability theory, which subsumes classical measurement theory as a special case, provides a general model for estimating the reliability of observational rating data by estimating the variance components of the measurement design. Research data from the "Heart Smart" health intervention program were analyzed as a heuristic tool.…