Meta-analytic structural equation modeling (MA-SEM) is increasingly being used to assess model-fit for variables' interrelations synthesized across studies. MA-SEM researchers have analyzed synthesized correlation matrices using structural equation modeling (SEM) estimation that is designed for covariance matrices. This can produce incorrect…

Teachers' perceptions of school climate in 59 elementary schools were assessed using a modified version of the School-Level Environment Questionnaire (SLEQ). Using structural equation modelling, a statistically significant, positive relationship was found between school mean teachers' perceptions of school climate and school mean student…

Recognizing recent criticisms concerning the cross-cultural generalizability of self-determination theory (SDT), the authors tested the SDT view that high school students in collectivistically oriented South Korea benefit from classroom experiences of autonomy support and psychological need satisfaction. In Study 1, experiences of autonomy,…

Although preventive interventions that include both parent and child components produce stronger effects on disruptive behavior than child-only interventions, engaging parents in behavioral parent training is a significant challenge. This study examined the effects of specific risk factors for child disruptive behavior on parent attendance in…

Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made…

This study examines prostitution, homelessness, delinquency and crime, and school problems as potential mediators of the relationship between childhood abuse and neglect (CAN) and illicit drug use in middle adulthood. Children with documented cases of physical and sexual abuse and neglect (ages 0-11) during 1967-1971 were matched with…

A general linear model (GLM) framework is used to suggest that structure coefficients ought to be interpreted in structural equation modeling confirmatory factor analysis (CFA) studies in which factors are correlated. The computation of structure coefficients in explanatory factor analysis and CFA is explained. Two heuristic data sets are used to…

Latent-class item response models with small numbers of latent classes are quite competitive in terms of model fit to corresponding item-response models, at least for one- and two-parameter logistic (1PL and 2PL) models. Provided that care is taken in terms of computational procedures and in terms of use of only limited numbers of latent classes,…

This paper presents a discussion of various statistical concepts and techniques in light of two propositions. The first is that researchers need to select analytical techniques that prevent them from committing Type VI errors, which are inconsistencies between the research question and the statistical analysis. The second is that many statistical…

Sample covariance matrices constructed with pairwise deletion for randomly missing data were used in a simulation with three sample sizes and five levels of missing data (up to 50%). Parameter estimates were unbiased, parameter variability was largely explicable, and no sample covariance matrices were nonpositive definite except for 50% missing…

Data from 180 British construction companies were collected to examine processes of organizational culture, cognition, and competition and their effects on organizational performance. Double-loop learning provided a competitive advantage and was most likely in competitive cultures, although cooperative cultures also increased performance.…

Describes an item response theory-based structural equation model that allows the short-term stability and the magnitude of retest effects to be assessed for some types of personality traits. Provides an empirical application of the model and discusses the substantive implications of the results. (SLD)

This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

Developed an EM type algorithm for maximum likelihood estimation of a general nonlinear structural equation model in which the E-step is completed by a Metropolis-Hastings algorithm. Illustrated the methodology with results from a simulation study and two real examples using data from previous studies. (SLD)

Total, direct, and indirect effects in linear structural equation models are examined. Formulas currently given for direct and total effects are reported, and causation is considered. It is concluded that in many instances the effects do not support the interpretations given in the literature. (SLD)