Mediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the limitation of this mediation testing method stems from its conservative Type I error, which reduces its statistical power and imposes certain constraints on its…

The present study integrates findings from three lines of research on the association of social cognition and externalizing psychopathology, language and externalizing psychopathology, and social cognition and language functioning using Structural Equation Modeling (SEM). To date these associations have been examined in pairs. A sample of 354…

This article discusses 5 approaches that secondary researchers might use to obtain robust estimates in structural equation modeling analyses when using data that come from large survey programs. These survey programs usually collect data using complex sampling designs and estimates obtained from conventional analyses that ignore the dependencies…

Applies the social relations model (SRM), designed to analyze nonindependent data, as a solution for studying the ways in which group members interrelate and influence one another that avoids some of the data analysis problems indigenous to group psychotherapy research. Discusses examples of applications of SRM to previously inaccessible research…

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

The logical flaw of using the methods of path analysis and structural equation modeling to make causative conclusions is demonstrated. A proper evaluation of the role of investigation versus experimentation is cited in the work of W. G. Cochran as explicated by D. R. Rubin (1983). (TJH)

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

Two-level data sets are frequently encountered in social and behavioral science research. They arise when observations are drawn from a known hierarchical structure, as when individuals are randomly drawn from groups that are randomly drawn from a target population. When the covariance structures in the group level and the individual level are the…

Single equation regression models have been used to test the effect of Supplemental Instruction (SI) on student retention. These models, however, fail to account for the two salient features of SI attendance and retention: (1) both SI attendance and retention are categorical variables, and (2) are jointly determined endogenous variables. Adopting…