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Comparison of Stopping Rules in Forward “Stepwise” Regression

Comparison of Stopping Rules in Forward “Stepwise” Regression Abstract This paper uses the unconditional mean square error of prediction as a criterion for comparing stopping rules used with the forward “stepwise” selection procedure in multivariate normal samples, based on simulations of 48 population correlation matrices. The CP statistic, “F to enter” (.15 < α < .25), a rule which minimizes the sample criterion, and one which sequentially tests the equality of the population criterion (.25 < α < .35) are superior. For these rules, the criterion seldom differs by more than three percent, although there are considerable differences between these and some of the other rules. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Statistical Association Taylor & Francis

Comparison of Stopping Rules in Forward “Stepwise” Regression

Comparison of Stopping Rules in Forward “Stepwise” Regression

Journal of the American Statistical Association , Volume 72 (357): 8 – Mar 1, 1977

Abstract

Abstract This paper uses the unconditional mean square error of prediction as a criterion for comparing stopping rules used with the forward “stepwise” selection procedure in multivariate normal samples, based on simulations of 48 population correlation matrices. The CP statistic, “F to enter” (.15 < α < .25), a rule which minimizes the sample criterion, and one which sequentially tests the equality of the population criterion (.25 < α < .35) are superior. For these rules, the criterion seldom differs by more than three percent, although there are considerable differences between these and some of the other rules.

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References (22)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1537-274X
eISSN
0162-1459
DOI
10.1080/01621459.1977.10479905
Publisher site
See Article on Publisher Site

Abstract

Abstract This paper uses the unconditional mean square error of prediction as a criterion for comparing stopping rules used with the forward “stepwise” selection procedure in multivariate normal samples, based on simulations of 48 population correlation matrices. The CP statistic, “F to enter” (.15 < α < .25), a rule which minimizes the sample criterion, and one which sequentially tests the equality of the population criterion (.25 < α < .35) are superior. For these rules, the criterion seldom differs by more than three percent, although there are considerable differences between these and some of the other rules.

Journal

Journal of the American Statistical AssociationTaylor & Francis

Published: Mar 1, 1977

Keywords: Stopping rules; Stepwise regression; Forward selection; Simulated correlation matrices

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