Presents solutions for the problem of maximizing the generalizability coefficient under a budget constraint. Shows that the Cauchy-Schwarz inequality can be applied to derive optimal continuous solutions for the number of conditions of each facet. Illustrates the formal similarity between optimization problems in survey sampling and…

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)

Classroom researchers are frequently urged to provide evidence of the reliability of their data. In the case of observational data, three approaches to this have emerged: observer agreement, generalizability theory, and measurement error. Generalizability theory provides the most powerful approach given an adequate data collection design, but…

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)

Evidence is presented on the generalizability and convergent validity of performance assessments using data from six studies of student achievement that sampled a wide range of measurement facets and methods. Results at individual and school levels indicate that task-sampling variability is the major source of measurement error. (SLD)

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.…

Classical test theory, item response theory, and generalizability theory all treat the abilities to be measured as continuous variables, and the items of a test as independent probes of underlying continua. These models are well-suited to measuring the broad, diffuse traits of traditional differential psychology, but not for measuring the outcomes…