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 its most basic form, latent growth modeling (latent curve analysis) allows an assessment of individuals' change in a measured variable X over time. For simple linear models, as with other growth models, parameter estimates associated with the a construct (amount of X at a chosen temporal reference point) and b construct (growth in X per unit…

Surveys at a university in Hong Kong indicated that graduates of discrete part-time programmes perceived significantly higher development in eight out of nine graduate capabilities than their counterparts in full-time programmes. Several possible explanations are considered and rejected. The conventional view that capabilities are nurtured through…

This article reviews several basic statistical tools needed for modeling data with sampling weights that are implemented in Mplus Version 3. These tools are illustrated in simulation studies for several latent variable models including factor analysis with continuous and categorical indicators, latent class analysis, and growth models. The…