Sensitivity analysis using an imputation method for missing binary data in clinical trials

被引：13
|
作者：
Proschan, MA [1 ]
McMahon, RP [1 ]
Shih, JH [1 ]
Hunsberger, SA [1 ]
Geller, NL [1 ]
Knatterud, G [1 ]
Wittes, J [1 ]
机构：
[1] NHLBI, Off Biostat Res, Rockledge Ctr 2, Bethesda, MD 20892 USA
来源：
JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2001年 / 96卷 / 01期
关键词：
missing data; multiple imputation; hypothesis testing; p-values;
D O I：
10.1016/S0378-3758(00)00332-3
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：
Missing data in clinical trials can result in biased treatment effect estimates and tests if the analysis includes only the observed data. Two simple methods of compensating for this potential bias in trials with a binary endpoint were suggested by Wittes et al. (Statist. Med. 8 (1989) 415-425). We study the statistical properties of these procedures and show that they are robust against certain model departures. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：155 / 165
页数：11
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