Typically, nonlinear models such as those used in the analysis of covariance structures, are not globally identifiable. Investigations of local identifiability must either yield a mapping onto the entire parameter space, or be confined to points of special interest such as the maximum likelihood point. (Author/JKS)

A method is developed for estimating the response time distribution of an unobserved component in a two-component serial model. The estimate of the component's density function is constrained to be only unimodal and non-negative. Numerical examples suggest the method can yield reasonably accurate estimates with sample sizes of 300. (Author/CTM)

The problem of comparing the latent abilities of groups of individuals (as opposed to their observable test scores) is considered. Tests of equality of means, variances, and longitudinal applications are discussed. (JKS)

A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)

Comparisons of subjects are specifically objective if they do not depend on the items involved. Such comparisons are not restricted to the one-parameter logistic latent trait model but may also be defined within ordinal independence models and even within the two-parameter logistic model. (Author)

A procedure is described for minimizing a class of matrix trace functions, which is a refinement of an earlier procedure for minimizing the class of matrix trace functions using majorization. Several trial analyses demonstrate that the revised procedure is more efficient than the earlier majorization-based procedure. (SLD)

The asymptotic standard deviation (SD) of the alpha coefficient with standardized variables is derived under normality. The research shows that the SD of the standardized alpha coefficient becomes smaller as the number of examinees and/or items increase. Furthermore, this research shows that the degree of the dependence of the SD on the number of…

Statistical methodology for handling omitted variables is presented in a multilevel modeling framework. In many nonexperimental studies, the analyst may not have access to all requisite variables, and this omission may lead to biased estimates of model parameters. By exploiting the hierarchical nature of multilevel data, a battery of statistical…

Several ways of using traditional analysis of variance to test the homogeneity of variance in factorial designs with equal or unequal cell sizes are compared using theoretical and Monte Carlo results. (Author/JKS)

A special case of Bloxom's version of Tucker's three mode factor analysis model is developed statistically. A goodness of fit test and an empirical example are presented. (Author/JKS)