a KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai, People's Republic of China
jason_xmh@163.com
a KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai, People's Republic of China;b Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
Abstract
We propose a constrained generalised method of moments (CGMM) for enhancing the efficiency of estimators in meta-analysis in which some studies do not measure all covariates associated with the response or outcome. Under some assumptions, we show that the proposed CGMM estimators have good asymptotic properties. We also demonstrate the effectiveness of the proposed method through simulation studies with fixed sample sizes.