Data evolving from processes which are developmental or hierarchical in nature are often analyzed by using latent class or latent structure models. A procedure for estimating such models when the model is not "identifiable" is presented. (JKS)

Estimation is by means of iterative convergence to maximum likelihood estimates, and two approaches to assessing fit of the model to sample data are discussed. Relation of this general probabilistic model to other, more restricted models is explored and three cases of the general model are applied to exemplary data. (Author/RC)

A probabilistic hypothesis testing procedure to assess the fit of hypothesized hierarchical structures for test item data is discussed. Statistical procedures are presented which are useful for evaluating the fit of data of a certain class of probabilistic models. These models apply to sets of dichotomous (O,1) responses for which there are…