Systematic evaluation and comparison of statistical tests for publication bias.
Systematic evaluation and comparison of statistical tests for publication bias.
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DOI：
10.2188/jea.15.235
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发表时间：
2005-11
影响因子：
4.7
通讯作者：
Fukui T
中科院分区：
文献类型：
--
作者：
Hayashino Y;Noguchi Y;Fukui T
背景技术背景：本研究评估了三种统计检验方法（Begg，Egger和Macaskill）的统计和区分能力，以检测荟萃分析中的发表偏倚。方法：数据来源是来自科克伦系统评价数据库2002年版的130篇综述，该数据库考虑了二元终点，包含10项或更多单独的研究。选择观察者同意的漏斗图作为参考标准。我们通过改变截止p值、给定固定假阳性率的统计检验的功效和受试者工作特征曲线下面积来评估灵敏度和特异性之间的权衡。结果：在36篇综述中，733项原始研究评估了2，874，006例受试者。每项研究纳入的试验数量范围为10 - 70（中位数14.5）。在假阳性率为0.1时，Egger法的灵敏度为0.93，大于Begg法（0.86）和Macaskill法（0.43）。三个统计检验的灵敏度随着临界值p值的增加而增加，而特异性没有显著降低。Egger法的ROC曲线下面积为0.955（95%可信区间0.889-1.000），与Begg法的ROC曲线下面积（area=0.913，p=0.2302）无差异，但大于Macaskill法的ROC曲线下面积（area=0.719，p=0.0116）。结论：Egger的线性回归方法和Begg的方法有更强的统计和歧视权力比Macaskill的方法检测出版物的偏见给予相同的I类错误水平。这些方法的功效可以通过增加截止p值而不显著增加假阳性率来提高。
BACKGROUND: This study evaluates the statistical and discriminatory powers of three statistical test methods (Begg’s, Egger’s, and Macaskill’s) to detect publication bias in meta-analyses. METHODS: The data sources were 130 reviews from the Cochrane Database of Systematic Reviews 2002 issue, which considered a binary endpoint and contained 10 or more individual studies. Funnel plots with observers’ agreements were selected as a reference standard. We evaluated a trade-off between sensitivity and specificity by varying cut-off p-values, power of statistical tests given fixed false positive rates, and area under the receiver operating characteristic curve. RESULTS: In 36 reviews, 733 original studies evaluated 2,874,006 subjects. The number of trials included in each ranged from 10 to 70 (median 14.5). Given that the false positive rate was 0.1, the sensitivity of Egger’s method was 0.93, and was larger than that of Begg’s method (0.86) and Macaskill’s method (0.43). The sensitivities of three statistical tests increased as the cut-off p-values increased without a substantial decrement of specificities. The area under the ROC curve of Egger’s method was 0.955 (95% confidence interval, 0.889-1.000) and was not different from that of Begg’s method (area=0.913, p=0.2302), but it was larger than that of Macaskill’s method (area=0.719, p=0.0116). CONCLUSION: Egger’s linear regression method and Begg’s method had stronger statistical and discriminatory powers than Macaskill’s method for detecting publication bias given the same type I error level. The power of these methods could be improved by increasing the cut-off p-value without a substantial increment of false positive rate.
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影响因子：
19.7
作者：
HANLEY, JA;MCNEIL, BJ
通讯作者：
MCNEIL, BJ
影响因子：
105.7
作者：
RAVNSKOV, U
通讯作者：
RAVNSKOV, U
影响因子：
1.9
作者：
DELONG, ER;DELONG, DM;CLARKEPEARSON, DI
通讯作者：
CLARKEPEARSON, DI
影响因子：
1.9
作者：
BEGG, CB;MAZUMDAR, M
通讯作者：
MAZUMDAR, M
影响因子：
105.7
作者：
GOTZSCHE, PC
通讯作者：
GOTZSCHE, PC