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一种用于随机临床试验中协方差分析的简单样本量计算公式。

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

作者信息

Borm George F, Fransen Jaap, Lemmens Wim A J G

机构信息

Department of Epidemiology and Biostatistics, Radboud University Nijmegen Medical Centre, Geert Grooteplein 21, PO Box 9101, NL-6500 HB Nijmegen, The Netherlands.

出版信息

J Clin Epidemiol. 2007 Dec;60(12):1234-8. doi: 10.1016/j.jclinepi.2007.02.006. Epub 2007 Jun 6.

Abstract

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 1-rho(2).

CONCLUSION

ANCOVA may considerably reduce the number of patients required for a trial.

摘要

目的

比较两种治疗方法对连续结果影响的随机临床试验可采用协方差分析(ANCOVA)或t检验方法进行分析。我们提出了一种在使用ANCOVA时计算样本量的方法。

研究设计与设置

我们推导了一个近似样本量公式。通过模拟来验证该公式的准确性,并改进小样本试验的近似值。在类风湿性关节炎的一项临床试验中展示了样本量的计算。

结果

如果基线测量结果与随访测量结果之间的相关性为rho,比较(1 - rho(2))n名受试者组的ANCOVA与比较n名受试者组的t检验具有相同的检验效能。在相同数据上,使用ANCOVA而非t检验时,治疗估计的精度会提高,置信区间的长度会缩短1 - rho(2)倍。

结论

ANCOVA可能会显著减少试验所需的患者数量。

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