Generalizability theory is based upon analysis of variance (ANOVA) and requires estimation of variance components for the ANOVA design under consideration in order to compute either G (Generalizability) or D (Decision) coefficients. Estimation of variance components has a number of alternative methods available using SAS, BMDP, and ad hoc procedures. This study examines the effect of these methods on coefficeints for a large sample of subjects under complex designs. The Wechsler Adult Intelligence Scale-Revised national standardization sample provided the data base. Subject (n=1880) variables (age, gender, etc.) provided variety for the construction of complex factoral designs. Three designs were used to investigate variance component estimation and resultant g-coefficeints. The designs included: (1) a two-factor subject x item design; (2) a three-factor subject x item x age design; and (3) a four-factor subject x item x age x gender design. These designs allowed estimation of both within and between subject effects. Suggestions are made concerning equal and unequal situations. (Author/PN)