Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by…

Three plausible assumptions of conditional independence in a hierarchical model for responses and response times on test items are identified. For each of the assumptions, a Lagrange multiplier test of the null hypothesis of conditional independence against a parametric alternative is derived. The tests have closed-form statistics that are easy to…

Blocked designs in functional magnetic resonance imaging (fMRI) are useful to localize functional brain areas. A blocked design consists of different blocks of trials of the same stimulus type and is characterized by three factors: the length of blocks, i.e., number of trials per blocks, the ordering of task and rest blocks, and the time between…

In this paper, we show that for some structural equation models (SEM), the classical chi-square goodness-of-fit test is unable to detect the presence of nonlinear terms in the model. As an example, we consider a regression model with latent variables and interactions terms. Not only the model test has zero power against that type of…

Although the "K"-means algorithm for minimizing the within-cluster sums of squared deviations from cluster centroids is perhaps the most common method for applied cluster analyses, a variety of other criteria are available. The "p"-median model is an especially well-studied clustering problem that requires the selection of "p" objects to serve as…

Conjoint choice experiments are used widely in marketing to study consumer preferences amongst alternative products. We develop a class of choice models, belonging to the class of Poisson race models, that describe a "random utility" which lends itself to a process-based description of choice. The models incorporate a dependence structure which…

When using linear models for cluster-correlated or longitudinal data, a common modeling practice is to begin by fitting a relatively simple model and then to increase the model complexity in steps. New predictors might be added to the model, or a more complex covariance structure might be specified for the observations. When fitting models for…

Recent advances in data recording technology have given researchers new ways of collecting on-line and continuous data for analyzing input-output systems. For example, continuous response digital interfaces are increasingly used in psychophysics. The statistical problem related to these input-output systems reduces to linking time-varying…

Presents a synthesis of the nominal categories model of R. Bock (1972) and the choice model for mixed-effects analysis of rank-ordered data by R. Luce (1959). Shows that the proposed ranking model is both parsimonious and flexible in accounting for preference heterogeneity as well as fixed and random effects of covariates. Discusses relationships…

Several probabilistic models for subset choice have been proposed in the literature, for example, to explain approval voting data. We show that Marley et al.'s latent scale model is subsumed by Falmagne and Regenwetter's size-independent model, in the sense that every choice probability distribution generated by the former can also be explained by…

A model for the utility of gambling that is based on Von Neumann-Morgenstern utility theory is proposed and analyzed. Aspects of the utility of gambling are noted, and comparisons are made to standard concepts of risk attitudes. (Author/JKS)

Presents a generalization and improvement for the definition proposed by E. Dzhafarov (2001) for selectiveness in the dependence of several random variables on several (sets of) external factors. This generalization links the notion of selective influence with that of conditional independence. (SLD)

Explored the use of additive tree models to represent set-symmetric distances for feature arrangements in set-theoretic or feature models. Studied arrangements of feature sets that have been proposed to represent qualitative and quantitative variation among objects in situations in which feature structures are defined in various ways. (SLD)

Recent attempts have been made to find a robust method for comparing the variances of "J" dependent random variables. However, these procedures can give unsatisfactory results. Several new procedures that are derived heuristically are examined. The most effective method is based on the statistic derived by D. Quade. (TJH)

General formulas are derived for assessing local influence under restrictions in which the first derivatives are still zeros, and then these results are applied to factor analysis, as the usually used restriction in factor analysis satisfies the conditions. (SLD)