Current computer programs for analyzing linear structural models will apparently handle only two types of constraints: fixed parameter and equal parameters. In this paper, a method for imposing several types of inequality of parameter constraints is described. Several examples are presented. (Author/JKS)

Canonical correlation analysis is considered to be a general model for bivariate and multivariate statistical methods. Some problems involving assumptions and statistical tests for parameters exist for social science data. A resolution for these problems is presented by treating canonical correlation as a special case of linear structural…

Structural equation modeling is applied in conjunction with constrained monotone distance analysis. These alternative methods are used in an evaluation of a social-psychological model derived from Likert's theory of organizational behavior. (Author/JKS)

Interpretations regarding the effects of exogenous and endogenous variables on endogenous variables in linear structural equation systems depend upon the convergence of a matrix power series. The test for convergence developed by Joreskog and Sorbom is shown to be only sufficient, not necessary and sufficient. (Author/JKS)

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)

This paper demonstrates the feasibility of using the penalty function method to estimate parameters that are subject to a set of functional constraints in covariance structure analysis. Both types of inequality and equality constraints are studied. The approaches of maximum likelihood and generalized least squares estimation are considered.…

A statistical model for relating latent variables from manifest variables, called a linear structural equation model, is presented. The approach is illustrated by a test theory model and longitudianl study of intelligence. (Author/JKS)

The Werts-Linn procedure for dealing with categorical errors of measurement in "Comments on Boyle's 'Path Analysis and Ordinal Data'" in The American Journal of Sociology, volume 76, number 6, May 1971, is shown to be inappropriate to the problem of ordered categories. (For related document, see TM 002 301.) (DB)

Presented is an approach to causal models in which some or all variables are discretely measured, showing that path analytic methods permit quantification of causal relationships among variables with the same flexibility and power of interpretation as is feasible in models including only continuous variables. Examples are provided. (Author/IS)

Early procedures for the analysis of multivariate panel data do not rest on well-specified statistical models. Recent approaches based on path analysis suffer from the defects of variable standardization and lack of attention to measurement error. The paper formulates a measurement model for quantitatively scaled multivariate panel data. The model…

This final report summarizes past research and suggests new approaches to the problem of estimating long-term individual constants using path analysis. The general objective of the research was to detect and measure the likelihood that one variable, x, measured at time, t, has a causal influence on another variable, y, measured at a subsequent…

Duncan's interpretation of his research on the nature and process of the distribution of rewards in the U.S. stratification system is questioned. Statistical and conceptual flaws are noted in Duncan's work and their implications explored. A reanalysis of primary survey data is presented and, based on a reinterpretation of this data, a…

Tries to develop a method for empirical evaluations of the impact of a school system on measurable cognitive and affective outcomes in students. Concentrates on the Partial Least Squares (PLS) methodology, and illustrates the potential of PLS for system analysis. (BW)