出版偏见
漏斗图
统计
荟萃分析
补语(音乐)
检验统计量
统计能力
秩(图论)
统计假设检验
计量经济学
样本量测定
数学
计算机科学
I类和II类错误
统计的
置信区间
医学
组合数学
生物化学
化学
互补
内科学
基因
表型
作者
Colin B. Begg,Madhuchhanda Mazumdar
出处
期刊:Biometrics
[Wiley]
日期:1994-12-01
卷期号:50 (4): 1088-1088
被引量:14675
摘要
An adjusted rank correlation test is proposed as a technique for identifying publication bias in a meta-analysis, and its operating characteristics are evaluated via simulations. The test statistic is a direct statistical analogue of the popular "funnel-graph." The number of component studies in the meta-analysis, the nature of the selection mechanism, the range of variances of the effect size estimates, and the true underlying effect size are all observed to be influential in determining the power of the test. The test is fairly powerful for large meta-analyses with 75 component studies, but has only moderate power for meta-analyses with 25 component studies. However, in many of the configurations in which there is low power, there is also relatively little bias in the summary effect size estimate. Nonetheless, the test must be interpreted with caution in small meta-analyses. In particular, bias cannot be ruled out if the test is not significant. The proposed technique has potential utility as an exploratory tool for meta-analysts, as a formal procedure to complement the funnel-graph.
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