We consider the estimation of probabilistic ranking models in the context of conjoint experiments. By using approximate rather than exact ranking probabilities, we avoided the computation of high-dimensional integrals. We extended the approximation technique proposed by Henery (1981) in the context of the Thurstone-Mosteller-Daniels model to any…

In this article, we directly question the common practice in growth mixture model (GMM) applications that exclusively rely on the fitting model without covariates for GMM class enumeration. We provide theoretical and simulation evidence to demonstrate that exclusion of covariates from GMM class enumeration could be problematic in many cases. Based…

The social accuracy model of interpersonal perception (SAM) is a componential model that estimates perceiver and target effects of different components of accuracy across traits simultaneously. For instance, Jane may be generally accurate in her perceptions of others and thus high in "perceptive accuracy"--the extent to which a particular…

Clusterwise linear regression is a multivariate statistical procedure that attempts to cluster objects with the objective of minimizing the sum of the error sums of squares for the within-cluster regression models. In this article, we show that the minimization of this criterion makes no effort to distinguish the error explained by the…

Individually randomized treatments are often administered within a group setting. As a consequence, outcomes for treated individuals may be correlated due to provider effects, common experiences within the group, and/or informal processes of socialization. In contrast, it is often reasonable to regard outcomes for control participants as…

This Monte Carlo study examined the impact of misspecifying the [big sum] matrix in longitudinal data analysis under both the multilevel model and mixed model frameworks. Under the multilevel model approach, under-specification and general-misspecification of the [big sum] matrix usually resulted in overestimation of the variances of the random…

This short contribution is a comment on M. Moerbeek's exploration of consequences of ignoring a level of clustering in a multilevel model, which was published in the first issue of the 2004 volume of Multivariate Behavioral Research. After having recapitulated the framework and extended the results of Moerbeek's study, we formulate two critical…

Alternative strategies for two-sample cross-validation of covariance structure models are described and investigated. Results of an empirical sampling study show that for tighter strategies simpler models are preferred in smaller samples, but when cross-validation is employed, a more complex model is supported even for small samples. (SLD)

Describes multilevel modeling of cognitive function in 70 subjects with schizophrenia, 115 of their healthy first-degree relatives, and 66 controls. Describes four methodological issues arising during data analysis and how multilevel modeling can be used, and discusses some cautions in the use of multilevel models. (SLD)

The source of an event-related brain potential (ERP) is estimated from multivariate measures of ERP on the head under several mathematical and physical constraints on the parameters of the source model. Statistical aspects of estimation are discussed, and new tests are proposed. (SLD)

This article presents a didactic discussion on the role of asymptotically independent test statistics and separable hypotheses as they pertain to issues of specification error, power, and model misspecification in the covariance structure modeling framework. A small population study supports the major findings. (SLD)

Using an approach to the analysis of missing data, this study investigated developmental trends in alcohol, marijuana, and cigarette use among 750 adolescents across 5 years using multiple-group latent growth modeling. Latent variable structural equation modeling and missing data approaches to studying developmental change are explored. (SLD)

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

This article describes the evolution of Raymond B. Cattell's data box (covariation chart), a synoptic conception of psychological data, from its introduction in 1946. Analytical techniques and related methodologies developed from this model by Cattell and other psychological researchers are discussed. (BS)

Findings are reported for a cross-validated study of factorial validity and invariance of the Maslach Burnout Inventory across gender for elementary school teachers (742 males and 801 females) and secondary school teachers (659 males and 721 females). The study illustrates structural modeling methodology and use of multiple model-fitting criteria.…