课题基金 / 基金详情

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

项目摘要

项目成果

Benedetti Andrea的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
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
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Recovering from the COVID-19 Pandemic, Informing Future Public Health Crises, and Building a Global Evidence Base for Mental Health Research: A Systematic Review of COVID-19-related Mental Health
Mental Health during the COVID-19 Pandemic: An Ongoing Living Systematic Review of Mental Health Burden and Intervention Effectiveness to Inform Management Strategies During and Post-COVID-19
Statistical Methodology for Prediction Modelling to Improve Depression Screening with Individualized Risk Estimates in the Context of Individual Participant Data Meta-analysis
Statistical Methodology for Prediction Modelling to Improve Depression Screening with Individualized Risk Estimates in the Context of Individual Participant Data Meta-analysis
海外基金