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 sources of error variance. If error influences interact, as they often will, the G-theory estimates may be markedly different from classical theory estimates. G-theory also distinguishes between relative and absolute decisions. Finally G-theory provides a mechanism for using estimated error variances for alternative designs (D-studies) to help researchers develop a measurement that minimizes error for a future study, but that is also efficient. Some of the major advantages of G-theory are explained and illustrated with a hypothetical study of 20 individuals given a performance task on 3 occasions and assessed by 2 raters. Three tables present data from the example. A five-item list of references is included. (Author/SLD)