It is demonstrated here that standardized regression coefficients greater than one can legitimately occur. Furthermore, the relationship between the occurrence of such coefficients and the extent of multicollinearity present among the set of predictor variables in an equation is examined. Comments on the interpretation of these coefficients are…

Path analysis is a data analytic technique for estimating the strengths of hypothesized relationships among a group of variables for a particular sample. Strategies for the use of path analysis are discussed in detail in this extensive article. (JKS)

The analytical procedure of path analysis is described in terms of its use in nonexperimental settings in the social sciences. The description assumes a moderate statistical background on the part of the reader. (JKS)

The usual interpretation of suppressor effects in a multiple regression equation assumes that the correlations among variables have been generated by a particular structural model. How such a regression equation is interpreted is shown to be dependent on the structural model deemed appropriate. (Author/JKS)

An example demonstrates that Joreskog's suggested sufficient conditions for identifying unknown parameters in a confirmatory factor analytic model with correlated factors are not sufficient. Sufficient conditions are presented. (Author/JKS)

Path analysis is presented as a technique that can be used to test on a priori model based on a theoretical conceptualization involving a network of selected variables. This being an introductory source, no previous knowledge of path analysis is assumed, although some understanding of the fundamentals of multiple regression analysis might be…

Sociological and demographic research often uses variables computed as ratios. When the denominators are highly correlated, and the ratios are used in correlation or regression analysis, a statistical dependency is formed. This article investigates this problem, particularly with respect to partial correlation, multiple regression, and the…

The use of a path analysis model to obtain unique, substantively meaningful decomposition of variance among endogenous (independent) variables in the model is argued. This reasoning runs counter to more traditional path analytic work. An example is provided. (Author/JKS)

A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…

The purpose of this paper is to illuminate the advantages of path analysis for the exposition of results in data analytic papers. Probably the greatest advantage is that it provides a means by which the nature of the problem may be handily summarized. The method of path analysis, although conceived over sixty years ago by Sewell Wright, has only…

The direct and indirect effects of neighborhood characteristics on school-level reading achievement were investigated via path analysis in this study. Race, family structure, income, and neighborhood density were among the variables investigated. (Author/JKS)

A Monte Carlo simulation was used to ascertain the degree of inflation that can occur in regression estimates when samples contain randomly occurring instances of a pattern among correlations called cooperative suppression. Ten thousand samples of scores on three variables were randomly drawn from a population in which the correlations among the…

The inclusion of unmeasured variables in path analyses in educational research is discussed. The statistical basis for inclusion is presented, along with several examples. (JKS)

Path analysis was used to reanalyze Kropp and Stoker's data from tests designed to evaluate Bloom's taxonomy of educational objectives in the cognitive domain. Scores for 1,128 students in grades nine through twelve were analyzed separately by grade level for four content areas on six taxonomic levels. A measure of general ability was also…

Path analysis, a technique related to multiple regression analysis is used for ascribing causal relationships among variables. Path analysis involves the construction of explicitly formulated causal models and makes the reasoning explicit in the form of path diagrams and structural equations. Regression analysis is then used to construct path…