An algorithm for obtaining initial values for the minimization process in covariance structure analysis is developed that is more generally applicable for computing parameters connected to latent variables than the currently existing ones. The algorithm is formulated in terms of the RAM model but can be extended. (SLD)

A reparameterization is formulated that yields estimates of scale-invariant parameters in recursive path models with latent variables, and (asymptotically) correct standard errors, without the use of constrained optimization. The method is based on the logical structure of the reticular action model. (Author)

Implications of ignoring correlated error on parameter estimates in some simple structural equation models are examined. It is shown analytically and empirically through simulation that ignoring positive between-construct correlated error overestimates the structural parameter linking the two constructs. Effects become more pronounced with…

A model which approaches the problem of characterizing distributions of test validity correlation coefficients from the perspective of finite mixture theory is presented. This estimation method offers advantages over validity generalization procedures. Examples are provided to illustrate applications of the method. (SLD)

Presents a LISREL model for the estimation of the repeated measures analysis of variance (ANOVA) with a patterned covariance matrix. The model is demonstrated for a 5 x 2 (Time x Group) ANOVA in which the data are assumed to be serially correlated. Similarities with the Statistical Analysis System PROC MIXED model are discussed. (SLD)

Point-estimate and confidence-interval procedures are proposed for the (1) combined Mann-Whitney U test; (2) combined two-sample normal-scores test; (3) combined matched-pair Wilcoxon signed-ranks test; and (4) combined matched-pair normal-scores test. The four techniques are illustrated with hypothetical examples and are considered either…

Monte Carlo methods were used to investigate the effect of misspecification of the second level in a two-level hierarchical linear model (HLM). Sample composition, heterogeneity of the group size, level of intraclass correlation, and correlation between second-level predictors were manipulated. Each of 20 generated data sets was analyzed nine…

The problem of combining information to estimate standardized partial regression coefficients in a linear model is considered. A combined estimate obtained from the pooled correlation matrix is proposed, and its large sample distribution is obtained. This estimate can be generalized to address situations in which not every study measures every…

A heuristic example is presented in which parsimony as typically operationalized in indices of fit may not be desirable. In a simplex model of longitudinal data, the failure to include correlated uniquenesses relating to the same indicators on different occasions will typically lead to systematically inflated estimates of stability. (SLD)

Conditions necessary and sufficient for the determination of LISREL model solutions are identified. The reasons for indeterminacy of LISREL solutions are discussed, and an index of determinacy is presented and related to the covariance matrix of latent variables. (SLD)

Section Pre-Equating (SPE) is a method used to equate test forms that consist of multiple separately timed sections. SPE does not require examinees to take two complete forms of the test. Instead, all of the old form and one or two sections of the new form are administered to each examinee, and missing data techniques are employed to estimate the…

Reparameterization is used to find the maximum likelihood estimates of parameters in a multivariate model having some component variable observable only in polychotomous form. Maximum likelihood estimates are found by a Fletcher Powell algorithm. In addition, the partition maximum likelihood method is proposed and illustrated. (Author/GDC)

Decomposable models, which allow for the interdependence of structure among observable variables, are described. Each model is fully characterized by a set of conditional interdependence restrictions and can be visualized with an undirected as well as a special type of directed graph. (Author/JKS)

The jackknife statistic is discussed as a viable invariance procedure. Data from a study of leadership illustrates the use of the jackknife in determining the stability of canonical function coefficients following canonical correlation analysis. The jackknife procedure entails arbitrarily omitting one observation or a subset of observations at a…

Using a Monte Carlo simulation, a bootstrap procedure was evaluated for setting a confidence interval on the unrestricted population correlation (rho) assuming various degrees of incomplete truncation on the predictor. Sample size was the most important factor in determining accuracy and stability. Sample size should be at least 50. (SLD)