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On the Relationship between the Johnson-Neyman Region of Significance and Statistical Tests of Parallel Within-Group Regressions.
Peer reviewed Peer reviewed
Rogosa, David – Educational and Psychological Measurement, 1981
The form of the Johnson-Neyman region of significance is shown to be determined by the statistic for testing the null hypothesis that the population within-group regressions are parallel. Results are obtained for both simultaneous and nonsimultaneous regions of significance. (Author)
Descriptors: Hypothesis Testing, Mathematical Models, Predictor Variables, Regression (Statistics)
Coding for Correlation and Regression
Peer reviewed Peer reviewed
Gocka, Edward F. – Educational and Psychological Measurement, 1974
Focuses on the procedures available for substituting a special predictive coding method for some of the more complex general regression procedures. (Author)
Descriptors: Analysis of Variance, Codification, Correlation, Predictor Variables
A Family of Multivariate Measures of Association for Nominal Independent Variables.
Peer reviewed Peer reviewed
Berry, Kenneth J.; Mielke, Paul W., Jr. – Educational and Psychological Measurement, 1992
A generalized measure of association and an associated test of significance are presented for nominal independent variables in which any number or combination of interval, ordinal, or nominal dependent variables can be analyzed. A permutation test of significance is provided for the new measure. (SLD)
Descriptors: Correlation, Equations (Mathematics), Mathematical Models, Multivariate Analysis
The Importance of Structure Coefficients in Regression Research.
Peer reviewed Peer reviewed
Thompson, Bruce; Borrello, Gloria M. – Educational and Psychological Measurement, 1985
Multiple regression analysis is frequently being employed in experimental and non-experimental research. However, when data include predictor variables that are correlated, some regression results can become difficult to interpret. This paper presents a study to provide a demonstration that structure coefficients may be useful in these cases.…
Descriptors: Correlation, Multiple Regression Analysis, Multivariate Analysis, Predictor Variables
Interactions Among Group Regressions: Testing Homogeneity of Group Regressions and Plotting Regions of Significance
Peer reviewed Peer reviewed
Borich, Gary D. – Educational and Psychological Measurement, 1971
Descriptors: Computer Programs, Hypothesis Testing, Interaction Process Analysis, Predictor Variables
A Test for Homogeneity of Regression without Homogeneity of Variance
Peer reviewed Peer reviewed
McLaughlin, Donald H. – Educational and Psychological Measurement, 1975
Develops a testing procedure based on a model including treatment effects on residual variances. (Author/RC)
Descriptors: Analysis of Variance, Aptitude Treatment Interaction, Hypothesis Testing, Interaction
Johnson-Neyman Revisited: Determining Interactions Among Group Regressions and Plotting Regions of Significance in the Case of Two Groups, Two Predictors, and One Criterion
Peer reviewed Peer reviewed
Borich, Gary D.; Wunderlich, Kenneth W. – Educational and Psychological Measurement, 1973
Descriptors: Analysis of Covariance, Computer Programs, Homogeneous Grouping, Input Output