Maximizing the Coefficient of Generalizability in Multi-Facet Decision Studies

For random-model, fully-crossed, two- and three-facet experimental designs the following two problems were considered. First, equations were developed for determining the optimal number of conditions of a facet for maximizing the coefficient of generalizability under the constraint that the total number of observations per subject is constant. Second, the problem of determining the minimum number of observations per subject for a specified generalizability coefficient is solved for the two-facet crossed design.