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A Bayesian Approach to the Selection of Predictor Variables NICHD

Author(s):
Novick, Melvin R.
Publication Year:
1969
Report Number:
RB-69-58
Source:
ETS Research Bulletin
Document Type:
Report
Page Count:
15
Subject/Key Words:
National Institute for Child Health and Human Development (NICHD), Bayesian Statistics, Lindley, D. V., Mathematical Models, Multiple Regression Analysis, Predictor Variables

Abstract

Some work of Lindley on a Bayesian structural model is shown to be relevant to the problem of the selection of predictor variables. It is suggested that estimates of regression parameters be regressed toward a mean value and that the resulting attenuated estimate of the multiple correlation be adopted. These regressed estimates are derived from a general Bayesian normal law analysis.

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