A simple sample size formula for analysis of covariance in randomized clinical trials

被引:399
作者
Borm, George F.
Fransen, Jaap
Lemmens, Wim A. J. G.
机构
[1] Radboud Univ Nijmegen Med Ctr, Dept Epidemiol & Biostat, NL-6500 HB Nijmegen, Netherlands
[2] Radboud Univ Nijmegen Med Ctr, Dept Rheumatol, NL-6500 HB Nijmegen, Netherlands
关键词
power; sample size; precision; analysis of covariance; clinical trial; statistical test;
D O I
10.1016/j.jclinepi.2007.02.006
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objective: Randomized clinical trials that compare two treatments on a continuous outcome can be analyzed using analysis of covariance (ANCOVA) or a t-test approach. We present a method for the sample size calculation when ANCOVA is used. Study Design and Setting: We derived an approximate sample size formula. Simulations were used to verify the accuracy of the formula and to improve the approximation for small trials. The sample size calculations are illustrated in a clinical trial in rheumatoid arthritis. Results: If the correlation between the outcome measured at baseline and at follow-up is rho, ANCOVA comparing groups of (1-rho(2))n subjects has the same power as t-test comparing groups of n subjects. When on the same data, ANCOVA is used instead of t-test, the precision of the treatment estimate is increased, and the length of the confidence interval is reduced by a factor root 1-rho(2). Conclusion: ANCOVA may considerably reduce the number of patients required for a trial. (C) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:1234 / 1238
页数:5
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