荟萃分析的结果对于告知环境政策和实践决策具有潜在的价值。然而,通过仅使用广泛使用的书目平台进行搜索的主要研究的选择性抽样可能会使效应大小的估计产生偏差.这种搜索策略在环境证据审查中很常见,如果可以检测到偏差的风险,这将提供第一个经验证据,证明搜索的全面性需要提高。我们比较了使用单个和多个书目平台搜索与更全面的搜索对平均效应大小估计的影响。我们使用了137个已发表的荟萃分析,基于多个源搜索,分析9388项研究:8095项来自商业发表的文章;1293项来自灰色文献和未发表的数据。单平台和多平台搜索在100和80个荟萃分析中错过了研究,分别为:52和46项荟萃分析提供了较大的效应估计值;32和28项荟萃分析提供了较小的效应估计值;8项和4项荟萃分析提供了相反的估计方向;2项荟萃分析均因缺失所有研究而无法估计效应.Further,我们发现遗漏研究的比例与平均效应大小的偏差之间存在显著的正对数线性关系,这表明,随着错过的研究数量的增加,平均效应大小的偏差可能会扩大。我们还发现,在35%的荟萃分析中,索引研究和非索引研究之间的平均效应大小存在显著差异。这表明,当搜索被限制时,偏倚的风险很高。我们得出的结论是,受限制的搜索很可能导致研究样本没有代表性,并且对真实效果的估计有偏差。
Results of meta-analyses are potentially valuable for informing environmental policy and practice decisions. However, selective sampling of primary studies through searches exclusively using widely used bibliographic platform(s) could bias estimates of effect sizes. Such search strategies are common in environmental evidence reviews, and if risk of bias can be detected, this would provide the first empirical evidence that comprehensiveness of searches needs to be improved. We compare the impact of using single and multiple bibliographic platform(s) searches vs more comprehensive searches on estimates of mean effect sizes. We used 137 published meta-analyses, based on multiple source searches, analyzing 9388 studies: 8095 sourced from commercially published articles; and 1293 from grey literature and unpublished data. Single-platform and multiple-platform searches missed studies in 100 and 80 of the meta-analyses, respectively: 52 and 46 meta-analyses provided larger-effect estimates; 32 and 28 meta-analyses provided smaller-effect estimates; eight and four meta-analyses provided opposite direction of estimates; and two each were unable to estimate effects due to missing all studies. Further, we found significant positive log-linear relationships between proportions of studies missed and the deviations of mean effect sizes, suggesting that as the number of studies missed increases, deviation of mean effect size is likely to expand. We also found significant differences in mean effect sizes between indexed and non-indexed studies for 35% of meta-analyses, indicating high risk of bias when the searches were restricted. We conclude that the restricted searches are likely to lead to unrepresentative samples of studies and biased estimates of true effects.