Statistics Meta-Analysis and the Related Research

Din Chen

UNC-Chapel Hill


Date: Wednesday, September 30, 2020
Time: 4:00 pm - 5:00 pm
Location: Virtual

Abstract: Meta-analysis is a statistical methodology to combine information from diverse studies to reach a more reliable and efficient conclusion. It can be performed by either synthesizing study-level summary statistics (SS) or modeling individual participant-level data (IPD), if available. However, it remains not fully understood whether the use of IPD indeed gains additional efficiency over SS. In this talk, we review the statistical meta-analysis and discuss the relative efficiency of the two methods under a general likelihood inference setting. We show theoretically that there is no gain of efficiency asymptotically by analyzing IPD, provided that the random-effects follow the Gaussian distribution and maximum likelihood estimation is used to obtain summary statistics. This is a joint work among Dungang Liu, Xiaoyi Min and Heping Zhang.

*All talks will be held virtually through Zoom.  Please contact for talk links.*