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A Comparison of Best Model Selection Criteria in Multiple Regression.
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Schumacker, Randall E. – 1994
The all-possible subset approach is recommended as an alternative over stepwise methods for selecting the best set of predictor variables for multiple regression. Several criteria are available for selecting the best subset model. These are compared with the principal component regression (PCR) method to investigate their usefulness for subset…
Descriptors: Comparative Analysis, Criteria, Models, Prediction
A Comparison of the Mallows' C subscript p and Principal Component Criteria for Best Model Selection in Multiple Regression.
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Schumacker, Randall E. – 1994
A population data set was randomly generated from which a random sample was drawn. This sample was randomly divided into two data sets, one of which was used to generate parameter estimates, which were then used in the second data set for cross-validation purposes. The best variable subset models were compared between the two data sets on the…
Descriptors: Comparative Analysis, Criteria, Estimation (Mathematics), Factor Analysis