The distributional characteristics of the Kaiser-Rice measure of sampling adequacy (MSA) were investigated with sample correlation matrices from multivariate normal populations where the level of correlation (LC) was systematically varied. Two additional variables were manipulated--sample size (SS) and number of variables (NV). Ten matrices were generated for each LC-SS-NV combination and the overall MSA computed for each, a total of 1,250. Significant effects were found for level of correlation and number of variables as well as for their interaction. Implications for applied factor analysis are discussed. (Author)