Publication bias poses a challenge for accurately synthesizing research findings using meta-analysis. A number of statistical methods have been developed to combat this problem by adjusting the meta-analytic estimates. Previous studies tended to apply these methods without regard to optimal conditions for each method’s performance. The present study sought to estimate the typical effect size attenuation of these methods when they are applied to real meta-analytic data sets that match the conditions under which each method is known to remain relatively unbiased (such as sample size, level of heterogeneity, population effect size, and the level of publication bias). Four-hundred and 33 data sets from 90 articles published in psychology journals were reanalyzed using a selection of publication bias adjustment methods. The downward adjustment found in our sample was minimal, with greatest identified attenuation of b = –.032, 95% highest posterior density interval (HPD) ranging from –.055 to –.009, for the precision effect test (PET). Some methods tended to adjust upward, and this was especially true for data sets with a sample size smaller than 10. We propose that researchers should seek to explore the full range of plausible estimates for the effects they are studying and note that these methods may not be able to combat bias in small samples (with less than 10 primary studies). We argue that although the effect size attenuation we found tended to be minimal, this should not be taken as an indication of low levels of publication bias in psychology. We discuss the findings with reference to new developments in Bayesian methods for publication bias adjustment, and the recent methodological reforms in psychology.

中文翻译：

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估计应用发表偏倚调整方法后荟萃分析效应大小估计值的变化。

发表偏见对使用荟萃分析准确综合研究结果提出了挑战。已经开发了许多统计方法来通过调整荟萃分析估计来解决这个问题。以前的研究倾向于应用这些方法，而不考虑每种方法性能的最佳条件。本研究试图估计这些方法在应用于真实荟萃分析数据集时的典型效应大小衰减，这些数据集与已知每种方法保持相对无偏的条件相匹配（例如样本大小、异质性水平、总体效应大小和发表偏倚水平）。使用一系列发表偏倚调整方法重新分析了心理学期刊上发表的 90 篇文章的 4033 个数据集。b = –.032，95% 最高后验密度区间 (HPD)，范围为 –.055 至 –.009，用于精密效果测试 (PET)。一些方法倾向于向上调整，对于样本量小于 10 的数据集尤其如此。我们建议研究人员应该寻求对他们正在研究的影响进行全面合理的估计，并注意这些方法可能不会能够消除小样本中的偏见（初步研究少于 10 项）。我们认为，尽管我们发现效应量衰减往往很小，但这不应被视为心理学发表偏倚水平较低的迹象。我们参考贝叶斯发表偏倚调整方法的新发展以及心理学最近的方法论改革来讨论这些发现。