Rules, procedures, and algorithms intended to aid researchers and practitioners in the application of generalizability theory to a broad range of measurement problems are presented. Two examples of measurement research are G studies, which examine the dependability of some general measurement procedure; and D studies, which provide the data for substantive decisions. Major emphasis is given to the estimation of G study variance components, and to the estimation and use of D study variance components for different objects of measurement and different universes of generalization. D studies in which the universe of generalization contains facets that are either fixed or essentially infinite are discussed, as well as D studies that involve sampling from a finite universe. A notational system is introduced to facilitate the discussion; and each rule, procedure or algorithm is illustrated using designs that involve varying types and degrees of complexity. (Author/MV)