marginal normality. Study I presents simulated data examples where the marginal normality assumption leads to a model that produces appropriate estimates only if subgroup differences are small. In the presence of larger subgroup differences that cannot be fitted by the marginal normality assumption, however, the proposed method produces subgroup mean and variance estimates that differ strongly from the true values. Study II extends the findings on the marginal normality estimates to real data from large scale assessment programs such as the National Assessment of Educational Progress (NAEP) and the National Adult Literacy Survey (NALS). The research presented in Study II shows differences between the two methods that are similar to the differences found in Study I. The consequences of relying upon the assumption of marginal normality in direct estimation are discussed.