Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

Using a Monte Carlo approach, comparison was made between traditional procedures and a multiple linear regression approach to test for differences between values of r sub 1 and r sub 2 when sample data were dependent and independent. For independent sample data, results from a z-test were compared to results from using multiple linear regression.…

The testing of contemporary sociological theory often calls for the application of structural-equation models to data which are inherently collinear. It is shown that simple ridge regression, which is commonly used for controlling the instability of ordinary least squares regression estimates in ill-conditioned data sets, is not a legitimate…

A Monte Carlo study was conducted to estimate the efficiency of and the relationship between five equations and the use of cross validation as methods for estimating shrinkage in multiple correlations. Two of the methods were intended to estimate shrinkage to population values and the other methods were intended to estimate shrinkage from sample…

The issues and some proposed solutions regarding Follow Through (FT) site variability are examined with a review of developments in FT evaluation. The role of adjusted site means with differences within sponsors and between sponsors and background characteristics is discussed to determine whether adjusted means are the preferred measures of model…

The accuracy and variability of 4 cross-validation procedures and 18 formulas were compared concerning their ability to estimate the population multiple correlation and the validity of the sample regression equation in the population. The investigation included two types of regression, multiple and stepwise; three sample sizes, N = 30, 60, 120;…

The effects of using different data analysis methods on estimates of treatment effects of educational programs were investigated. Various regression models, such as those recommended for Title I program evaluations, were studied. The first effect studied was the amount of bias that might be expected to occur in the various settings. Results…

Discriminant analysis is reviewed in terms of: (1) formulations, (2) interpretations, (3) uses, (4) issues and problems in applications, (5) recent developments and conceptualizations, and (6) general references and computer programs. Four aspects of a discriminant analysis are considered. They are: (1) separation: determining intergroup…

To determine the factors that influence interpretation of a research study description, 8 descriptions of research studies were interpreted by 320 undergraduate students in psychology, mathematics, and economics statistics and research methods classes at the University of Victoria (British Columbia, Canada), Millersville University (Pennsylvania),…