Provides an overview of the issue's special section on structural equation modeling, indicating what the section contains and what it omits. (Author/RH)

Caution is advised in utilizing the univariate F test as the initial screening device for hypothesis testing in the analysis of repeated measures data. (JMB)

Three role-taking tasks assessing children's ability to infer another's intentions, thoughts, and feelings were adapted for videotaped presentation and used to examine the coherence of role-taking abilities. Subjects were 110 second grade boys and girls. (Author/JMB)

Examines and rejects common criticisms of the causality concept; shows causality is a relation implied in the grammar of a language about objects. Discusses objective criteria for concepts of causal relations and explains how the concept of causality may be modified to have causes determine probabilities of outcomes. (Author/RH)

Provides a set of guidelines for evaluating research using structural equation modeling (SEM). Offers insight into how someone familiar with SEM would judge the adequacy of a study using such methods. (Author/RH)

Demonstrates ways in which conclusions about models may be affected by violations of the assumption that the observed variables are normally distributed. Addresses the issue of the robustness of findings obtained under such conditions. (Author/RH)

Two statistical characteristics of the Matching Familiar Figures test which produce methodological problems in reflection-impulsivity research are discussed. (BRT)

Challenges the typical treatment of causal effects in longitudinal data, arguing that models should be conceptualized and tested in ways that directly reflect prior assumptions as to the trait- or state-like nature of the variables. Examples demonstrate that meaningful longitudinal studies of state variables can be conducted without assuming their…

The intent of this paper is to demonstrate that the standard age effect in analysis of variance provides an ineffective means of assessing developmental change when several age levels are involved and a roughly monotonic trend can be expected. (Author)

Introduces structural modeling with nonnormal continuous variables, using the equations language of the micro-mainframe program EQS in the context of a longitudinal study of adolescent development that followed about 700 adolescents across an 8-year span into young adulthood. Two models are developed to assess the influence of drug use on…

Considers problems which arise when researchers do not have the optimally large sample sizes desired in structural equation modeling. Discusses the ways in which small sample size affects assessment of model fit. Provides a new estimator that may be beneficial for use in small-sample situations. (Author/RH)

The conventional analysis of variance applied to designs in which each subject is measured repeatedly requires stringent assumptions regarding the variance-covariance structure of the data. This paper considers alternatives when heterogeneity of covariance exists, including nonparametric tests, randomization and matching procedures, Box and…

Defines structural equation modeling (SEM) and points out its relation to other more familiar data-analytic techniques, as well as some of the potentials and pitfalls of SEM in the analysis of developmental data. Discussion focuses on causal modeling, path diagrams, ordinary least-squares regression analysis, and powerful methods for model…

An analysis using data drawn from Nancy Bayley's Berkeley Growth Study is performed for didactic purposes to illustrate the use of structural equation modeling on a child development data set. Alternatives to standard latent factor approaches are demonstrated for use in research situations in which the subject-to-variable ratio is less than…