The univariate and multivariate models for the analysis of covariance are compared for the case where an experimental design contains between and within subject factors, one dependent variable, and one observation per subject. (Author/JKS)

The effects of several specification search strategies used with Covariance Structure Modeling to obtain more parsimonious models are examined. The initial models vary in their degree of "correctness." Restricting modifications to those justified by prior theoretical knowledge improves the success of a specification search. (TJH)

Classification is a procedure through which individuals are classified as being members of a particular group based on a variety of independent variables. Two methods of makin such classifications are discussed; the quadratic method is seen to be superior to the linear under certain constraints. (JKS)

Guilford's structure of intellect model and an alternative model were compared using oblique and orthogonal factors. Using covariance structure analysis it was found that the fit of the oblique Guilford model was better than that of the alternative oblique model. (Author/RL)

Describes a method for automated parameter estimation and testing of fit of nonstandard models for mean vectors and covariance matrices, allowing for nonlinear equality and inequality constraints on model parameters. Users need only provide subroutines to evaluate mean vector and covariance matrix according to the model and constraint functions.…

A general statistical model for the multivariate analysis of mean and covariance structures is described. Matrix calculus is used to develop the statistical aspects of one new special case in detail. This special case separates the confounding of principal components and factor analysis. (DEP)

Factor analysis in several populations, covariance structure models, three-mode factor analysis, structural equations systems with measurement model, and analysis of covariance with measurement model are all shown to be specializations of a general moment structure model. Some new structured linear models are also described. (Author/CTM)

The use of analysis of covariance in conjunction with the multivariate approach to analyzing repeated measures designs is considered for designs involving between- and within-subject factors, one dependent variable, and one observation per subject on the covariate. (Author/RL)

The empirical performance under null/alternative hypotheses of the likelihood ratio difference test (LRDT); Lagrange Multiplier test (evaluating the impact of model modification with a specific model); and Wald test (using a general model) were compared. The new tests for covariance structure analysis performed as well as did the LRDT. (RLC)

A bivariate generalization of the genotype-environment covariation (GEC) is presented. A multivariate procedure for detecting univariate and bivariate GEC is also described and illustrated via a study of 136 adopted and 125 non-adopted 4-year-old children. (SLD)

Procedures for simultaneous confirmatory factor analysis in several populations are useful in a variety of problems. This is demonstrated with examples involving missing data, comparison of part correlations between groups, testing the equality of regression weights between groups with multiple indicators of each variable, and the formulation of…

Three frequently used response formats are compared via analysis of covariance structures. The cumulative results based on four data sets provided evidence inconsistent with previous research suggesting that these formats are interchangeable. The semantic-differential format is most preferred while in most cases the Stapel format is least…

Variance formulas of H. E. Daniels and M. G. Kendall (1947) are generalized to allow for the presence of ties and variance of the sample tau correlation. Applications of these generalized formulas are discussed and illustrated using data from a 1965 study of contraceptive use in 15 developing countries. (SLD)