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Meta-analysis of independent datasets using constrained generalised method of moments

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  • Menghao Xu
  • Jun Shao

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.

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  • Menghao Xu & Jun Shao, 2020. "Meta-analysis of independent datasets using constrained generalised method of moments," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 4(1), pages 109-116, July.
    • Handle: RePEc:taf:tstfxx:v:4:y:2020:i:1:p:109-116
    DOI: 10.1080/24754269.2019.1630545
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