Balanced versus unbalanced designs for linear structural relations in two‐level data

A general two‐level model for multivariate data is described and illustrated by specializations to a common factor model and a path model with latent variables. The problem of estimation is treated, and in the special case of a balanced sampling design, a likelihood‐based discrepancy function and a test of goodness of fit are obtained in terms of some simple sufficient statistics.