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 relationship between quantitative predictor variables and the probability of occurrence of one or more levels of a qualitative criterion variable can be analyzed by quantal response techniques. This paper presents and discusses two quantal response models, comparing them to multiple linear regression and discriminant analysis. (Author/JKS)

A suppressor variable is a regressor in a multiple regression which contributes more to the squared multiple correlation than the magnitude of its simple correlation with the outcome variable. An example of such a situation is provided for teaching purposes. (JKS)

An existing computer program for computing multiple regression analyses is made interactive in order to alleviate core storage requirements. Also, some improvements in the graphics aspects of the program are included. (JKS)

An artifact encountered in regression models of human judgment is explored. The direction and magnitude of the artifactual effect is shown to depend upon the nature of the experimental task and task conditions. Use of an alternative index is recommended. (Author/JKS)

The relationship between the factor structure of a convariance matrix and the factor structure of a partial convariance matrix when one or more variables are partialled out of the original matrix is given in this brief note. (JKS)

Econometric techniques for estimating the parameters of individual and group multi-attribute utility models are discussed. These techniques permit measurement of intra-and inter-individual heterogeneity with regard to the importance ascribed to the model attributes. (Author/JKS)

EXPLORE is a flexible computer program for analyzing multiple data sets. The investigator has the option of focusing on the original variables, or of selecting a reduced rank solution where original variables are summarized by a principal components analysis. (Author/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)

Taking multidimensional life satisfaction as the basic premise of this study, a four-equation multiple regression model was constructed for its prediction. Results indicated that the pattern of regressor influence varied greatly between equations, providing fairly specific evidence on a number of previously espoused hypotheses. (Author)

Multivariate selection can be represented as a linear transformation in a geometric framework. In this note this approach is extended to describe the effects of selection on regression analysis and to adjust for the effects of selection using the inverse of the linear transformation. (Author/BW)

Multiple regression analysis (MRA) may be used when both continuous and categorical variables are included as independent research variables. The use of MRA with categorical variables involves dummy coding, that is, assigning zeros and ones to levels of categorical variables. Caution is urged in results interpretation. (Author/CH)

This note proposes an alternative implementation of the regression method which should be slightly faster than the principal components methods for estimating missing data. (RC)

Several procedures are outlined for replacing missing values in multivariate analyses by regression values obtained in various ways, and for adjusting coefficients (such as factor score coefficients) when data are missing. None of the procedures are complex or expensive. (Author)

It is shown that in the special case of just two criterion groups the predictor variables may be equivalently ordered (with respect to contribution to prediction or discrimination) by the univariate F-ratios and by estimates of the predictor versus the linear discriminant function correlations. (Author)