Variable Selection for Logistic Regression Using a Prediction Focussed Information Criterion

22 Pages Posted: 23 Jan 2006

See all articles by Gerda Claeskens

Gerda Claeskens

KU Leuven - Department of Economics

Christophe Croux

Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES); Catholic University of Leuven (KUL) - Department of Applied Economics

Johan Van Kerckhoven

Katholieke Universiteit Leuven (KUL)

Abstract

In biostatistical practice, it is common to use information criteria as a guide for model selection. We propose new versions of the Focussed Information Criterion (FIC) for variable selection in logistic regression. The FIC gives, depending on the quantity to be estimated, possibly different sets of selected variables. The standard version of the FIC measures the Mean Squared Error (MSE) of the estimator of the quantity of interest in the selected model. In this paper we propose more general versions of the FIC, allowing other risk measures such as one based on Lp-error. When prediction of an event is important, as is often the case in medical applications, we construct an FIC using the error rate as a natural risk measure. The advantages of using an information criterion which depends on both the quantity of interest and the selected risk measure are illustrated by means of a simulation study and application to a study on diabetic retinopathy.

Keywords: Error rate, Focussed information criterion, Forward selection, Logistic regression, Model selection, Risk measures

Suggested Citation

Claeskens, Gerda and Croux, Christophe and Van Kerckhoven, Johan, Variable Selection for Logistic Regression Using a Prediction Focussed Information Criterion. Available at SSRN: https://ssrn.com/abstract=876597 or http://dx.doi.org/10.2139/ssrn.876597

Gerda Claeskens (Contact Author)

KU Leuven - Department of Economics ( email )

Leuven, B-3000
Belgium

Christophe Croux

Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES) ( email )

Ave. Franklin D Roosevelt, 50 - C.P. 114
Brussels, B-1050
Belgium

Catholic University of Leuven (KUL) - Department of Applied Economics ( email )

Leuven, B-3000
Belgium

Johan Van Kerckhoven

Katholieke Universiteit Leuven (KUL) ( email )

Oude Markt 13
Leuven, Vlaams-Brabant 3000
Belgium

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