Structural equation modeling is used in the simultaneous study of individual and group latent change patterns on several longitudinally assessed variables. The approach, which is based on a special case of the comprehensive latent curve analysis of W. Meredith and J. Tisak (1990), is illustrated with a two-group study. (SLD)

Methods are offered for conducting hypothesis testing associated with disattenuated validity coefficients to overcome limitations of some other suggested approaches. Through using classical test theory's notion of reliability in the form of structured path models, such hypothesis testing may be done with hierarchically related structural equation…

Reviews the use of structural equation modeling for providing an overall assessment of mediation, the mechanism that accounts for the relation between the predictor and the criterion. A strategy for supplemental details is presented that measures the magnitude of mediational effects. (SLD)

Simulation results show that the power to detect small mean differences when fitting a model with free residual variances across groups decreases as the difference in R squared increases. This decrease is more pronounced in the presence of correlated errors and if group sample sizes differ. (SLD)

Reexamined the nature of structural equation modeling (SEM) estimates of autoregressive moving average (ARMA) models, replicated the simulation experiments of P. Molenaar, and examined the behavior of the log-likelihood ratio test. Simulation studies indicate that estimates of ARMA parameters observed with SEM software are identical to those…

Studied the use of different weighting techniques in structural equation modeling and found, through simulation, that the use of an effective sample size weight provides unbiased estimates of key parameters and their sampling variances. Also discusses use of a popular normalization technique of scaling weights. (SLD)

This article presents a straightforward classification system that is a necessary and sufficient condition for identification of the structural component of structural equation models of the block-recursive type with no more than two equations per block. Limitations of other identification techniques are discussed. (SLD)

Describes two strategies for assessing measures of practical fit and the goodness of fit from structural equation models. Focuses on linear structural relations (LISREL), chi-square fit index, practical fit indices, and hierarchical analyses. Includes empirical example of hierarchical model procedures used with practical and statistical indices to…

Explores the four-step procedure for testing structural equation models and outlines some problems with the approach advocated by L. Hayduk and D. Glaser (2000) and S. Mulaik and R. Milsap (2000). Questions the idea that there is a "correct" number of constructs for a given phenomenon. (SLD)

Describes the integration of programmatic theory and structural equation modeling to serve as the basic intellectual machinery for designing and evaluating behavioral interventions. Illustrates this integration with the example of a program to reduce sexual risk taking. (SLD)

Simulated data for factor analytic models is used in the evaluation of three methods for controlling Type I errors: (1) the standard approach that involves testing each parameter at the 0.05 level; (2) the Bonferroni approach; and (3) a simultaneous test procedure (STP). Advantages offered by the Bonferroni approach are discussed. (SLD)

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)