Focuses on the four-step method (four nested models) of structural equation modeling advocated by S. Mulaik (1997, 1998), discussing the limitations of the approach and considering the tests and criteria to be used in moving among the four steps. (SLD)

Defends the four-step approach to structural equation modeling based on testing sequences of models and points out misunderstandings of opponents of the approach. The four-step approach allows the separation of respective constraints within a structural equation model. (SLD)

Neither the four-step model nor the one-step procedure can actually tell whether the researcher has the right number of factors in structural equation modeling. In fact, for reasons discussed, a simple formulaic approach to the correct specification of models does not yet exist. (SLD)

Replies to commentaries on the four-step approach to structural equation modeling, pointing out the strengths and weaknesses of each argument and ultimately concluding that the four-step model is subject to criticisms that can be addressed to factor analysis as well. (SLD)

Evaluated the bootstrap method under varying conditions of nonnormality, sample size, model specification, and number of bootstrap samples drawn from the resampling space. Results for the bootstrap suggest the resampling-based method may be conservative in its control over model rejections, thus having an impact on the statistical power associated…

The relationship between attention and general intelligence was investigated considering the different types of attention: alertness, sustained attention, focused attention, attentional switching, divided attention, attention according to the supervisory attentional system, attention as inhibition, spatial attention, attention as planning,…

This article illustrates the use of the SAS system for Monte Carlo simulation work in structural equation modeling (SEM). Data generation procedures for both multivariate normal and nonnormal conditions are discussed, and relevant SAS codes for implementing these procedures are presented. A hypothetical example is presented in which Monte Carlo…

The aim of this study was to present and initially test a model of escalation to verbal and physical aggression among Israeli youths. Stratified sampling was used to obtain data from 799 students in the 7th, 8th, and 9th grades of junior high schools in a northern Israeli city and its suburbs. A structural equation model (SEM) analysis confirmed…

To date, finite mixtures of structural equation models (SEMMs) have been developed and applied almost exclusively for the purpose of providing model-based cluster analyses. This type of analysis constitutes a direct application of the model wherein the estimated component distributions of the latent classes are thought to represent the…

A covariance structure modeling method to test equality in proportions explained variance in studied unobserved dimensions by means of latent predictors is outlined. The procedure is applicable with multiple-indicator, structural equation models where of interest is to compare the predictive power of sets of latent independent variables for given…

Quality of life (QOL) has become an important concept for health care. As QOL is a multidimensional concept that is best evaluated by a number of latent constructs, it is well recognized that latent variable models, such as exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are useful tools for analyzing QOL data. Recently,…

Structural Equation Modeling techniques were used to clarify the relationship between marital characteristics, marital processes, and the dependent variable--marital satisfaction--in a sample of 201 participants who were in 1st marriages. The Dyadic Adjustment Scale (DAS; G. B. Spanier, 1976) and the Enriching and Nurturing Relationship Issues,…

Information fit indexes such as Akaike Information Criterion, Consistent Akaike Information Criterion, Bayesian Information Criterion, and the expected cross validation index can be valuable in assessing the relative fit of structural equation models that differ regarding restrictiveness. In cases in which models without mean restrictions (i.e.,…

Structural equation modeling (SEM) has become increasingly popular for analyzing data in the social sciences, although several broad reviews of psychology journals suggest that many SEM researchers engage in questionable practices when using the technique. The purpose of this study is to review and critique the use of SEM in counseling psychology…

The four reactions in the May 2005 issue of "The Counseling Psychologist" address several considerations regarding the use of structural equation modeling (SEM) in counseling psychology research, including its appropriateness for analyzing one's data and testing one versus multiple theoretical models. In addition, points that are not mentioned in…