This paper, in a fashion easy to follow, illustrates the interesting relationship between structural equation modeling and canonical correlation analysis. Although computationally somewhat inconvenient, representing canonical correlation as a structural equation model may provide some information which is not available from conventional canonical…

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…

This paper provides an introduction to basic issues concerning structural equation modeling (SEM), a research methodology increasingly being used in social science research. First, seven key issues that must be considered in any SEM analysis are explained. These include matrix of associations to analyze, model identification, parameter estimation…

This paper describes structural equation modeling (SEM) in comparison with another overarching analysis within the general linear model (GLM) analytic family: canonical correlation analysis. The uninitiated reader can gain an understanding of SEM's basic tenets and applications. Latent constructs discovered via a measurement model are explored and…

A Monte Carlo simulation study was conducted to investigate the effects of sample size, estimation method, and model specification on structural equation modeling (SEM) fit indices. Based on a balanced 3x2x5 design, a total of 6,000 samples were generated from a prespecified population covariance matrix, and eight popular SEM fit indices were…

Suggests that the ability to process narrative information is fundamental to understanding human psychological development. Notes that a culture's system of understanding and interpreting the world is carried mostly by stories and texts. Explores how narrative understanding can be modeled in Fuzzy Trace Theory by using the principles of this…

A Monte Carlo study was conducted to assess the effects of some potential confounding factors on structural equation modeling (SEM) fit indices and parameter estimates for both true and misspecified models. The factors investigated were data nonnormality, SEM estimation method, and sample size. Based on the fully crossed and balanced 3x3x4x2…

Illustrates some of the analytic tools and conventions associated with the construction and evaluation of dynamic models of the processes underlying learning, memory, and development. Describes a study finding that children may exhibit slower disintegration of verbatim memory traces than adults due to interference; however, adults may be more…

Reviews efforts to develop mathematical models in developmental psychology. Explores recent developments in using dynamical systems for modeling human psychological processes. Comments on the studies described in this journal issue on dynamic modeling of cognitive development. Suggests that using this framework holds great promise for clarifying…

Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…

Proposes a new conceptual framework, embedded in a dynamic model, that accounts for children's failure to reason transitively. Examines five different models of transitive reasoning. Develops a model of how children initially represent and then use the ordered information available in the transitive inference model and how these processes change…

The impact of the use of data arising from balanced incomplete block (BIB) spiralled designs on the chi-square goodness-of-fit test in factor analysis is considered. Data from BIB designs posses a unique pattern of missing data that can be characterized as missing completely at random (MCAR). Standard approaches to factor analyzing such data rest…

Several goodness of fit (GOF) criteria have been developed to assist the researcher in interpreting structural equation models. However, the determination of GOF for structural equation models is not as straightforward as that for other statistical approaches in multivariate procedures. The four GOF criteria used across the commonly used…