A technique is presented which applies the Neyman theory of confidence intervals to interval estimation of the squared multiple correlation coefficient. A computer program is presented which can be used to apply the technique. (Author/JKS)

Using a recent innovation described by Pedhazur, a simpler regression solution to the repeated measures design is shown. Use of the techniques is described and an example is presented. (Author/JKS)

A class of monotonic transformations which generalize the power transformation is fit to the independent and dependent variables in multiple regression so that the resulting additive relationship is optimized. Examples of analysis of real and artificial data are presented. (Author/JKS)

A family of solutions for linear relations among k sets of variables is proposed. Solutions are compared with respect to their optimality properties. For each solution the appropriate stationary equations are given. For one example it is shown how the determinantal equation of the stationary equations can be interpreted. (Author/BW)

The index of redundancy is a measure of association between a set of independent variables and a set of dependent variables. Properties and interpretations of redundancy variables, in a particular subset of the original variables, are discussed. (JKS)

Commonality components have been defined as a method of partitioning squared multiple correlations. The asymptotic joint distribution of all possible squared multiple correlations is derived. The asymptotic joint distribution of linear combinations of squared multiple correlations is obtained as a corollary. (Author/JKS)

This paper details a Bayesian alternative to the use of least squares and equal weighting coefficients in regression. An equal weight prior distribution for the linear regression parameters is described with regard to the conditional normal regression model, and resulting posterior distributions for these parameters are detailed. (Author/CTM)

Guttman's assumption underlying his definition of "total images" is rejected. Partial images are not generally convergent everywhere. Even divergence everywhere is shown to be possible. The convergence type always found on partial images is convergence in quadratic mean; hence, total images are redefined as quadratic mean-limits.…

An extension of Wollenberg's redundancy analysis (an alternative to canonical correlation) is proposed to derive Y-variates corresponding to the optimal X-variates. These variates are maximally correlated with the given X-variates, and depending upon the standardization chosen they also have certain properties of orthogonality. (Author/JKS)

Assuming a multiple linear regression model with q independent variables, a procedure is developed for determining the minimum statistically significant increase in the multiple correlation coefficient when an additional independent variable is considered for regression. The procedure is presented analytically and in table form. Examples are…

The squared multiple correlation of a variable with the remaining variables in a variable set is shown to be a function of the communalities and the squared canonical correlations between the observed variables and common factors. (Author/JKS)

Semipartial correlation is one of several ways of determining the relative importance of independent variables in a multiple regression analysis. A veteran teacher of statistics and related topics explains his reasons for avoiding semipartial correlations. (SV)

In a conjoint-analysis consumer-preference study, researchers must determine whether the product factor estimates, which measure consumer preferences, should be calculated and interpreted for each respondent or collectively. Multiple regression models can determine whether to aggregate data by examining factor-respondent interaction effects. This…