Longitudinal structural equation modeling (SEM) can be a basis for making prescriptive statements on educational practice and offers yields over "traditional" statistical techniques under the general linear model. The extent to which prescriptive statements can be made will rely on the appropriate accommodation of key elements of research design,…

This article links the structural equation modeling (SEM) approach with the principal stratification (PS) approach, both of which have been widely used to study the role of intermediate posttreatment outcomes in randomized experiments. Despite the potential benefit of such integration, the 2 approaches have been developed in parallel with little…

Purpose: The purpose of this paper is to investigate whether students' perceptions of their school environment and their adjustment to school are associated with health outcomes across gender and age groups. Design/methodology/approach: Data from the cross-sectional international Health Behavior in School-aged Children Survey of the year 2002…

This paper concerns the divisibility of comprehension subskills measured in L2 listening and reading tests. Motivated by the administration of the new Web-based English as a Second Language Placement Exam (WB-ESLPE) at UCLA, this study addresses the following research questions: first, to what extent do the WB-ESLPE listening and reading items…

To synthesize studies that use structural equation modeling (SEM), researchers usually use Pearson correlations (univariate r), Fisher z scores (univariate z), or generalized least squares (GLS) to combine the correlation matrices. The pooled correlation matrix is then analyzed by the use of SEM. Questionable inferences may occur for these ad hoc…

The choice of constraints used to identify a simple factor model can affect the shape of the likelihood. Specifically, under some nonzero constraints, standard errors may be inestimable even at the maximum likelihood estimate (MLE). For a broader class of nonzero constraints, symmetric normal approximations to the modal region may not be…

Two methods, direct maximum likelihood (ML) and the expectation maximization (EM) algorithm, can be used to obtain ML parameter estimates for structural equation models with missing data (MD). Although the 2 methods frequently produce identical parameter estimates, it may be easier to satisfy missing at random assumptions using EM. However, no…

This study tested two theoretical models of perceived understanding as a potential mediator of perceived teacher confirmation and students' ratings of instruction. Participants included 651 undergraduate students who completed survey measures. Results of structural equation modeling provided greater support for the confirmation process model,…