A bound for publication bias based on the fraction of unpublished studies
A bound for publication bias based on the fraction of unpublished studies
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DOI：
10.1111/j.0006-341x.2004.00161.x
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发表时间：
2004-03-01
期刊：
影响因子：
1.9
通讯作者：
Jackson, D
中科院分区：
文献类型：
--
作者：
Copas, J;Jackson, D
Meta分析中的发表偏差通常通过接受/拒绝选择程序来模拟，在接受/拒绝选择过程中，选定的研究是“已发表”的研究，拒绝的研究是“未发表”的研究。一种可能的选择机制是假设只有报告估计治疗效果超过(或低于)某个阈值的研究才被接受。我们表明，在适当选择阈值的情况下，这在所有选择机制中达到最大偏差，其中选择的概率随着研究规模的增加而增加。仅从观察到的研究来估计选择机制是不可能的：这一结果导致了对发表偏差的“最坏情况”敏感性分析，这在实践中非常容易实施。该方法是使用预防性皮质类固醇有效性的数据来说明的。
Publication bias in meta-analysis is usually modeled in terms of an accept/reject selection procedure in which the selected studies are the "published" studies and the rejected studies are the "unpublished" studies. One possible selection mechanism is to suppose that only studies that report an estimated treatment effect exceeding (or falling short of) some threshold are accepted. We show that, with appropriate choice of thresholds, this attains the maximum bias among all selection mechanisms in which the probability of selection increases with study size. It is impossible to estimate the selection mechanism from the observed studies alone: this result leads to a "worst-case" sensitivity analysis for publication bias, which is remarkably easy to implement in practice. The method is illustrated using data on the effectiveness of prophylactic corticosteroids.