A quadratic bootstrap method and improved estimation in logistic regression

被引:11
作者
Claeskens, G
Aerts, M
Molenberghs, G
机构
[1] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA
[2] Limburgs Univ Ctr, Ctr Stat, B-3590 Diepenbeek, Belgium
关键词
bias correction; bootstrap confidence interval; one-step bootstrap; logistic regression;
D O I
10.1016/S0167-7152(02)00397-8
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper presents a quadratic one-step bootstrap method for binary response data. Rather than resampling from the original sample, the proposed method resamples summands appearing in the quadratic approximation of the estimates. It enjoys the same computational simplicity as its linear analogue while being more accurate. Moreover it allows the construction of a bias corrected estimator and improved confidence intervals, A small simulation study illustrates the improved finite sample behaviour for binary response data. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:383 / 394
页数:12
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