Additive and non-additive models for an individual trend curve are examined, and five methods for fitting these to a set of individuals are described. It is suggested that classical fitting methods are more informative than latent curve methods, and commonly preferable. A limited study of the effect of time-structure is reported, and results on…

A general model for two-level multivariate data, with responses possibly missing at random, is described. The model combines regressions on fixed explanatory variables with structured residual covariance matrices. The likelihood function is reduced to a form enabling computational methods for estimating the model to be devised. (Author)

It is shown that goodness-of-fit criteria developed for the evaluation of multivariate structural models can be applied to assist in evaluating the dimensionality of a test consisting of binary items, and correlative methods regularly used in factor analysis can be employed to diagnose causes of misfit. (Author)