Introduction Single-facet Designs Multifacet Universes of Admissible Observations and G Study Designs Multifacet Universes of Generalization and D Study Designs Advanced Topics in Univariate Generalizability Theory Variability of Statistics in Generalizability Theory Unbalanced Random Effects Designs Unbalanced Random Effects Designs--Examples Multivariate G Studies Multivariate D Studies Multivariate Regressed Scores
Introduction * Single-facet Designs * Multifacet Universes of Admissible Observations and G Study Designs * Multifacet Universes of Generalization and D Study Designs * Advanced Topics in Univariate Generalizability Theory * Variability of Statistics in Generalizability Theory * Unbalanced Random Effects Designs * Unbalanced Random Effects Designs--Examples * Multivariate G Studies * Multivariate D Studies * Multivariate Regressed Scores
Generalizability theory offers an extensive conceptual framework and a powerful set of statistical procedures for characterizing and quantifying the fallibility of measurements. Robert Brennan, the author, has written the most comprehensive and up-to-date treatment of generalizability theory. The book provides a synthesis of those parts of the statistical literature that are directly applicable to generalizability theory. The principal intended audience is measurement practitioners and graduate students in the behavioral and social sciences, although a few examples and references are provided from other fields. Readers will benefit from some familiarity with classical test theory and analysis of variance, but the treatment of most topics does not presume specific background.
Generalizability theory is an area of statistics with application to measurement in psychology and education. The main audience is measurement practitioners and graduate students in the behavorial and social sciences. Professor Brennan has been President of the National Council on Measurement in Education and has received awards for outstanding technical contributions to educational measurement.