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Inter-Inventory Predictability and Content Overlap of the 16PF and the CPI
Peer reviewed Peer reviewed
Campbell, John B.; Chun, Ki-Taek – Applied Psychological Measurement, 1977
A multiple regression approach is used to assess the feasibility of reciprocal prediction between the Sixteen Personality Factor Questionnaire scales and the California Psychological Inventory scales (i.e., the prediction of each 16PF scale from the CPI scales and of each CPI scale from the 16PF scales). (RC)
Descriptors: Correlation, Multiple Regression Analysis, Personality Measures, Prediction
Multiple Regression and Validity Estimation in One Sample.
Peer reviewed Peer reviewed
Claudy, John G. – Applied Psychological Measurement, 1979
Equations for estimating the value of the multiple correlation coefficient in the population underlying a sample and the value of the population validity coefficient of a sample regression equation were investigated. Results indicated that cross-validation may no longer be necessary for certain purposes. (Author/MH)
Descriptors: Correlation, Mathematical Formulas, Multiple Regression Analysis, Predictor Variables
Estimators of the Squared Cross-Validity Coefficient: A Monte Carlo Investigation.
Peer reviewed Peer reviewed
And Others; Drasgow, Fritz – Applied Psychological Measurement, 1979
A Monte Carlo experiment was used to evaluate four procedures for estimating the population squared cross-validity of a sample least squares regression equation. One estimator was particularly recommended. (Author/BH)
Descriptors: Correlation, Least Squares Statistics, Mathematical Formulas, Multiple Regression Analysis
The Use of Structural Equation Models in Interpreting Regression Equations Including Suppressor and Enhancer Variables.
Peer reviewed Peer reviewed
McFatter, Robert M. – Applied Psychological Measurement, 1979
The usual interpretation of suppressor effects in a multiple regression equation assumes that the correlations among variables have been generated by a particular structural model. How such a regression equation is interpreted is shown to be dependent on the structural model deemed appropriate. (Author/JKS)
Descriptors: Correlation, Critical Path Method, Data Analysis, Models