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Statistical challenges in individual patient data meta analysis

Statistical challenges in individual patient data meta analysis
个体患者数据荟萃分析的统计挑战
批准号：
290977
负责人：
Benedetti Andrea
金额：
$13.79万
依托单位：
Research Institute of the McGill University Health Centre
依托单位国家：
加拿大
项目类别：
Operating Grants
财政年份：
2013
资助国家：
加拿大
项目状态：
已结题
起止时间：
2013-09-01 至 2016-09-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=290977&lang=en
关键词：
Biostatistical Methods Drug Resistance Epidemiology Generalized Linear Mixed Models Heterogeneity Individual Patient Data Meta Analysis Linear Mixed Models Meta Analysis Surgery Tuberculosis

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中文摘要
翻译
个体患者数据被认为是荟萃分析方法中的黄金标准，荟萃分析方法试图将来自许多研究的联合收割机证据结合成一个信息。IPD-MA使用每个患者的逐行数据，而不是典型的聚合数据元数据，
英文摘要
Individual patient data are considered the gold-standard among meta-analytic methods, which attempt to combine evidence from many studies into one message. An IPD-MA uses line-by-line data for each patient, in contrast to a typical, aggregate-data meta-an
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