Common applications of the part correlation coefficient are in causal regression models and estimation of suppressor variable effects. However, there is no statistical test of the significance of the difference between a zero-order correlation and a part correlation, nor between a pair of part correlations. Hotelling's t is used for contrasting:…

A Monte Carlo study was conducted to discover the amount of bias to be expected in canonical correlations and in the canonical redundancy statistic. Six hundred random sample replications of 72 conditions were performed and the mean sample values compared with population values. Conditions were varied with respect to the number of predictor…

This description of the technical details required for using the HIER-GRP computer program, which was developed to group or cluster regression equations in an iterative manner so as to minimize the overall loss of predictive efficiency at each iteration, contains a discussion of the basic algorithm, an outline of the essential steps,…

The intention of this paper is to provide an overall reference on how a researcher can apply multiple linear regression in order to utilize the advantages that it has to offer. The advantages and some concerns expressed about the technique are examined. A number of practical ways by which researchers can deal with such concerns as…

Several statistical techniques that can be used to ameliorate the difficulties inherent in the data analysis of longitudinal studies are presented. The first step in longitudinal data analysis is graphing. This permits visual inspection of the data, and with educated viewing can yield insights into the nature of the underlying mechanisms. The next…

Two well known directional (one-tailed) tests of significance, mean difference and correlation coefficient, are presented within the multiple linear regression framework. Adjustments on the computed probability level are indicated. The case for a directional interaction research hypothesis is defended. Conservative adjustments on the computed…

This paper introduces a model for describing outliers (observations which are extreme in some sense or violate the apparent pattern of other observations) in linear regression which can be viewed as a mixture of a quadratic and a linear regression. The maximum likelihood estimators of the parameters in the model are derived and their asymptotic…

Fixed-width confidence intervals for a population regression line over a finite interval of x have recently been derived by Gafarian. The method is extended to provide fixed-width confidence intervals for the difference between two population regression lines, resulting in a simple procedure analogous to the Johnson-Neyman technique. (Author)

Focuses on developing a systematic characterization of the error forms resulting from model misspecification in single equation models for least squares regression analyses. (Author/DEP)

Readability formulas are designed to provide quantitative estimates of the relative difficulty of pieces of writing. This study explored the extent to which an increase in the accuracy of a specific readability formula could be obtained by norming it for a restricted set of reading materials and subjects. (Editor)

A definition of a suppressor variable is presented which is based on the relation of the semipartial correlation to the zero order correlation. Advantages of the definition are given. (Author/JKS)

The effects of the violation of the assumption of normality in the conditional distributions of the dependent variable, coupled with the condition of multicollinearity upon the outcome of testing the hypothesis that the regression coefficient equals zero, are investigated via a Monte Carlo study. (Author/JKS)

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)