The radial plot in meta-analysis: approximations and applications
The radial plot in meta-analysis: approximations and applications
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DOI：
10.1111/j.1467-9876.2008.00650.x
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发表时间：
2009-01-01
影响因子：
1.6
通讯作者：
Lozada-Can, Claudia
中科院分区：
文献类型：
--
作者：
Copas, John;Lozada-Can, Claudia
固定效应荟萃分析可以被认为是径向图的最小二乘分析，即标准化处理效果对精度（标准差的倒数）的图，用于系统评价研究。例如，通过原点的最小二乘斜率估计处理效果，广泛使用的发表偏倚检验相当于检验回归截距的显著性。然而，通常的理论假设研究内的差异是已知的，而在实践中，它们是估计的。这将导致径向图中点的额外可变性，从而导致从这些回归计算中得出的推论出现明显的失真。Cochrane数据库中的一个临床试验例子说明了这一点。我们推导了径向图抽样特性的近似值，并建议对一些常用的meta分析方法进行偏差修正。一项模拟研究表明，这些偏差校正在控制检验的显著性水平和置信区间的覆盖率方面是有效的。
Fixed effects meta-analysis can be thought of as least squares analysis of the radial plot, the plot of standardized treatment effect against precision (reciprocal of the standard deviation) for the studies in a systematic review. For example, the least squares slope through the origin estimates the treatment effect, and a widely used test for publication bias is equivalent to testing the significance of the regression intercept. However, the usual theory assumes that the within-study variances are known, whereas in practice they are estimated. This leads to extra variability in the points of the radial plot which can lead to a marked distortion in inferences that are derived from these regression calculations. This is illustrated by a clinical trials example from the Cochrane database. We derive approximations to the sampling properties of the radial plot and suggest bias corrections to some of the commonly used methods of meta-analysis. A simulation study suggests that these bias corrections are effective in controlling levels of significance of tests and coverage of confidence intervals.