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临床试验荟萃分析的随机效应模型:最新进展

Random-effects model for meta-analysis of clinical trials: an update.

作者信息

DerSimonian Rebecca, Kacker Raghu

机构信息

Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA.

出版信息

Contemp Clin Trials. 2007 Feb;28(2):105-14. doi: 10.1016/j.cct.2006.04.004. Epub 2006 May 12.

Abstract

The random-effects model is often used for meta-analysis of clinical studies. The method explicitly accounts for the heterogeneity of studies through a statistical parameter representing the inter-study variation. We discuss several iterative and non-iterative alternative methods for estimating the inter-study variance and hence the overall population treatment effect. We show that the leading methods for estimating the inter-study variance are special cases of a general method-of-moments estimate of the inter-study variance. The general method suggests two new two-step methods. The iterative estimate is statistically optimal and it can be easily calculated on a spreadsheet program, such as Microsoft Excel, available on the desktop of most researchers. The two-step methods approximate the optimal iterative method better than the earlier one-step non-iterative methods.

摘要

随机效应模型常用于临床研究的荟萃分析。该方法通过一个代表研究间变异的统计参数明确考虑了研究的异质性。我们讨论了几种用于估计研究间方差从而估计总体人群治疗效果的迭代和非迭代替代方法。我们表明,估计研究间方差的主要方法是研究间方差的一般矩估计法的特殊情况。该一般方法提出了两种新的两步法。迭代估计在统计上是最优的,并且可以很容易地在大多数研究人员桌面上都有的电子表格程序(如Microsoft Excel)上进行计算。与早期的一步非迭代方法相比,两步法能更好地逼近最优迭代方法。

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