Resampling tests for meta-analysis of ecological data
Resampling tests for meta-analysis of ecological data
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DOI：
10.2307/2265879
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发表时间：
1997-06-01
期刊：
影响因子：
4.8
通讯作者：
Rosenberg, MS
中科院分区：
文献类型：
--
作者：
Adams, DC;Gurevitch, J;Rosenberg, MS
荟萃分析是一种统计技术，它允许人们将多个研究的结果结合起来，以收集对各种现象总体重要性的推断。这种方法可以证明比常见的“投票计数”提供更多的信息，在“投票计数”中，将重要结果的数量与不重要结果的数量进行比较，以确定感兴趣的现象是否具有全局重要性。虽然元分析的使用在医学和社会科学中很普遍，但直到最近才被应用于生态问题。我们将通常通过荟萃分析获得的参数置信限和同质统计数据的结果与重新抽样方法获得的结果进行了比较，以确定标准荟萃分析技术的稳健性。我们发现基于自举方法的置信限比标准置信限更宽，这意味着重抽样估计更保守。此外，我们发现基于同质性统计的显著性检验偶尔与随机化检验的结果不同，这意味着仅基于卡方显著性检验的推论可能导致错误的结论。我们的结论是，重新抽样方法应纳入荟萃分析研究，以确保正确评估生态研究中的主要效应。
Meta-analysis is a statistical technique that allows one to combine the results from multiple studies to glean inferences on the overall importance of various phenomena. This method can prove to be more informative than common ''vote counting,'' in which the number of significant results is compared to the number with nonsignificant results to determine whether the phenomenon of interest is globally important. While the use of metaanalysis is widespread in medicine and the social sciences, only recently has it been applied to ecological questions. We compared the results of parametric confidence limits and homogeneity statistics commonly obtained through meta-analysis to those obtained from resampling methods to ascertain the robustness of standard meta-analytic techniques. We found that confidence limits based on bootstrapping methods were wider than standard confidence limits, implying that resampling estimates are more conservative. In addition, we found that significance tests based on homogeneity statistics differed occasionally from results of randomization tests, implying that inferences based solely on chi-square significance tests may lead to erroneous conclusions. We conclude that resampling methods should be incorporated in meta-analysis studies, to ensure proper evaluation of main effects in ecological studies.