夸大证据：荟萃分析中的重复计算及相关问题。
Overstating the evidence: double counting in meta-analysis and related problems.
作者信息
Senn Stephen J
机构信息
Department of Statistics, University of Glasgow, Glasgow, UK.
出版信息
BMC Med Res Methodol. 2009 Feb 13;9:10. doi: 10.1186/1471-2288-9-10.
BACKGROUND
The problem of missing studies in meta-analysis has received much attention. Less attention has been paid to the more serious problem of double counting of evidence.
METHODS
Various problems in overstating the precision of results from meta-analyses are described and illustrated with examples, including papers from leading medical journals. These problems include, but are not limited to, simple double counting of the same studies, double counting of some aspects of the studies, inappropriate imputation of results, and assigning spurious precision to individual studies.
RESULTS
Some suggestions are made as to how the quality and reliability of meta-analysis can be improved. It is proposed that the key to quality in meta-analysis lies in the results being transparent and checkable.
CONCLUSION
Existing quality check lists for meta-analysis do little to encourage an appropriate attitude to combining evidence and to statistical analysis. Journals and other relevant organisations should encourage authors to make data available and make methods explicit. They should also act promptly to withdraw meta-analyses when mistakes are found.
背景
荟萃分析中研究缺失的问题已受到广泛关注。而证据重复计算这一更为严重的问题却较少受到关注。
方法
描述并举例说明了夸大荟萃分析结果精度的各种问题，包括来自顶尖医学期刊的论文。这些问题包括但不限于对同一研究的简单重复计算、对研究某些方面的重复计算、结果的不恰当估算以及赋予个别研究虚假的精度。
结果
就如何提高荟萃分析的质量和可靠性提出了一些建议。有人提出，荟萃分析质量的关键在于结果透明且可核查。
结论
现有的荟萃分析质量检查表对鼓励以恰当态度合并证据和进行统计分析作用不大。期刊及其他相关组织应鼓励作者公开数据并明确方法。发现错误时，还应及时撤回荟萃分析。
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