Accession Number : ADA186032

Title :   Variable Selection in Logistic Regression.

Descriptive Note : Technical rept.,

Corporate Author : PITTSBURGH UNIV PA CENTER FOR MULTIVARIATE ANALYSIS

Personal Author(s) : Bai, Z D ; Krishnaiah, P R ; Zhao, L C

PDF Url : ADA186032

Report Date : Jun 1987

Pagination or Media Count : 20

Abstract : In many situations, we are interested in selection of important variables which are adequate for prediction under a logistic regression model. In this paper, some selection procedures based on the information theoretic criteria are proposed, and these procedures are proved to be strongly consistent. Keywords: Maximum likelihood estimation; Multivariate analysis; Asymptotic expansion.

Descriptors :   *REGRESSION ANALYSIS, *VARIABLES, ASYMPTOTIC SERIES, INFORMATION THEORY, LOGISTICS, MATHEMATICAL MODELS, MAXIMUM LIKELIHOOD ESTIMATION, SELECTION, MULTIVARIATE ANALYSIS, MATHEMATICAL PREDICTION

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE