Presents a new approach that extends conventional random coefficient growth models to incorporate a categorical latent trajectory variable representing latent classes or mixtures. Provides a didactic example of this new methodology using adolescent alcohol use data and discusses the method as a tool for mapping hypotheses of development onto…

Proposes the use of nonnested tests for the two stage least squares (2SLS) estimator of latent variable models to discriminate between scales. Compares the finite sample performance of these tests to structural equation modeling information-based criteria. Presents practical recommendations based on the Monte Carlo analysis. (SLD)

Uses a confirmatory factor analytic (CFA) model as a paradigmatic basis for the comparison of three widely used structural equation modeling computer programs: (1) AMOS 4.0; (2) EQS 6; and (3) LISREL 8. Comparisons focus on aspects of programs that bear on the specification and testing of CFA models and the treatment of incomplete, nonnormally…

In separate studies, 121 high school students and 127 adults completed the Career Decision-Making Difficulties Questionnaire. Its multidimensional structure was confirmed and the model of career decision making fit both groups. The adults reported fewer difficulties on all subscales. (Contains 60 references.) (SK)

Provides an introduction to latent growth modeling (LGM), a branch of structural equation modeling that facilitates the evaluation of longitudinal change. Fundamental concepts related to growth modeling and notation are introduced; and variations, extensions, and applications of the technique are discussed. Touts LGM's versatility when considering…

Studied the maximum likelihood estimation of unknown parameters in a general LISREL-type model with mixed polytomous and continuous data through Monte Carlo simulation. Proposes a model selection procedure for obtaining good models for the underlying substantive theory and discusses the effectiveness of the proposed model. (SLD)

We consider power calculation in structural equation modeling with data missing completely at random (MCAR). Muth?n and Muth?n (2002) recently demonstrated how power calculations with data MCAR can be carried out by means of a Monte Carlo study. Here we show that the method of Satorra and Saris (1985), which is based on the nonnull distribution of…

This paper presents the results of 3 studies examining the relationships of parental attachment, peer attachment, and self-esteem to adolescent psychological health. A model is presented in which parental attachment directly influences both psychological health and self-esteem and the influence of peer attachment on psychological health is totally…

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

Interactions between (multiple indicator) latent variables are rarely used because of implementation complexity and competing strategies. Based on 4 simulation studies, the traditional constrained approach performed more poorly than did 3 new approaches-unconstrained, generalized appended product indicator, and quasi-maximum-likelihood (QML). The…

The latent trait-state-error model (TSE) and the latent state-trait model with autoregression (LST-AR) represent creative structural equation methods for examining the longitudinal structure of psychological constructs. Application of these models has been somewhat limited by empirical or conceptual problems. In the present study, Monte Carlo…

This article is concerned with the seemingly simple problem of testing whether latent factors are perfectly correlated (i.e., statistically indistinct). In recent literature, researchers have used different approaches, which are not always correct or complete. We discuss the parameter constraints required to obtain such perfectly correlated latent…

In this article, a case-deletion procedure is proposed to detect influential observations in a nonlinear structural equation model. The key idea is to develop the diagnostic measures based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm. An one-step pseudo approximation is proposed to reduce the…

Structural equation models are presented as alternative models for examining longitudinal data. The models include (a) a cross-lagged regression model, (b) a factor model based on latent growth curves, and (c) a dynamic model based on latent difference scores. The illustrative data are on motivation and perceived competence of students during…

Beginning with Version 11, SPSS implemented the MIXED procedure, which is capable of performing many common hierarchical linear model analyses. The purpose of this article was to provide a tutorial for performing cross-sectional and longitudinal analyses using this popular software platform. In doing so, the authors borrowed heavily from Singer's…