This paper describes structural equation modeling (SEM) in comparison with another overarching analysis within the general linear model (GLM) analytic family: canonical correlation analysis. The uninitiated reader can gain an understanding of SEM's basic tenets and applications. Latent constructs discovered via a measurement model are explored and…

This simulation study focused on the power of detecting group differences in linear growth trajectory parameters within the framework of structural equation modeling (SEM) and compared this approach with the more traditional repeated measures analysis of variance (ANOVA) approach. Three broad conditions of group differences in linear growth…

A didactic example is presented of the application of new developments in structural equation modeling that allow for the modeling of multilevel data. The method, a synthesis of methods developed by B. Muthen, is applied to the problem of validating indicators of science education quality in the United States. (SLD)

The SEPATH structural equation modeling (SEM) software is a new module in the latest release of STATISTICA (version 5.0) for Windows 3.1 and Windows 95. SEPATH is a program that provides a comprehensive set of functions for the SEM modeling. The interface and the Monte Carlo capability are strong features. (SLD)

Relative fit indices using the null model as the reference point in computation may differ across estimation methods, as this article illustrates by comparing maximum likelihood, ordinary least squares, and generalized least squares estimation in structural equation modeling. The illustration uses a covariance matrix for six observed variables…

Multiple-group structural equation modeling was used to analyze structural relationships between latent factors underlying measures of handwriting, spelling, and composing for students in grades one through six. Results with 300 children show that the mechanical skills of writing may constrain the amount and quality of composing. (SLD)

Examined several hypotheses about the suitability of the noncentral chi square in applied research using Monte Carlo simulation experiments with seven sample sizes and three distinct model types, each with five specifications. Results show that, in general, for models with small to moderate misspecification, the noncentral chi-square is well…

Structural equation modeling of data from 4,034 Canadian adolescents yielded a factor composed of academic achievement, extracurricular reading, attitudes toward school and homework, and parental educational expectations that predicted 76% of variance in educational aspirations. Positive family climate and parental involvement fostered a positive…

Using two-level structural equation modeling, examined the dimensionality of socioeconomic status (SES) and its relationship with mathematics and science performance at student and school levels. Data from 13-year-olds from the Third International Mathematics and Science Study show that SES dimensions have different effects on mathematics and…

Developed a Bayesian approach for structural equation models with ignorable missing continuous and polytomous data that obtains joint Bayesian estimates of thresholds, structural parameters, and latent factor scores simultaneously. Illustrated the approach through analysis of a real data set of 20 patterns of condom use in the Philippines. (SLD)

A maximum-likelihood confirmatory factor analysis was performed by applying LISREL VII to the Wechsler Adult Intelligence Scale-Revised results of a normal elderly sample of 225 adults. Results indicate that a three-factor model fits best across all sample combinations. A mild gender effect is discussed. (SLD)

Benefits and limitations of structural equation models for multivariate experiments with incomplete data are presented. Examples from studies of latent variable path models of cognitive performance illustrate analyses with latent variables, omitted variables, randomly missing data, and nonrandomly missing data. (SLD)

Describes method of analysis of the relation between working alliance and therapeutic outcome using hierarchical linear modeling. Results revealed a significant association between linear growth function of therapist ratings of working alliance and therapeutic outcome. Discusses need to conceptualize working alliance as a temporally variant, as…

Discusses linear structural relations, Two Stage Least Squares, and path analysis as statistical procedures that sometimes permit causal inferences from correlational findings. Even though two variables cannot be interpreted causally due to a possible but unknown third variable, these methods are appropriate for handling models with correlated…

Defines structural equation modeling as comprehensive, flexible approach to research design and data analysis. Provides conceptual overview of clinical research hypotheses that invite evaluation as structural equation models. Particular attention is devoted to hypotheses that are not adequately evaluated using traditional statistical models.…