统计与管理学院2015年学术报告第34期

【主  题】 Meta-Analysis: Is There an Efficiency Gain by Using Original Data?

【报告人】 Lin Danyu 教授

Department of Biostatistics，University of North Carolina at Chapel Hill

【时  间】 2015年7月08日（星期三）15:00－16:00

【地  点】 上海财经大学统计与管理学院大楼1208室

【语  言】 英文

【摘  要】 Meta-analysis is widely used to synthesize the results of multiple studies. Although meta-analysis is traditionally carried out by combining the summary statistics of relevant studies, advances in technologies and communications have made it increasingly feasible to access the original data on individual participants.  We investigate the relative efficiency of analyzing original data versus combining summary statistics. We show that, for all commonly used parametric and semiparametric models, there is no asymptotic efficiency gain by analyzing original data if the parameter of main interest has a common value across studies; when the parameter of main interest follows a random-effect distribution, the maximum likelihood estimation of original data can be even less efficient than combining summary statistics. We demonstrate these theoretical results using both simulated and real data.