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Jackknife empirical likelihood method for multiply robust estimation with missing data
1Department of Biostatistics and Epidemiology, University of Oklahoma, Health Sciences Center, Oklahoma City, Oklahoma 73104, USA.
Abstract:
A novel jackknife empirical likelihood method for constructing confidence intervals for multiply robust estimators is proposed in the context of missing data. Under mild regularity conditions, the proposed jackknife empirical likelihood ratio has been shown to converge to a standard chi-square distribution. A simulation study supports the findings and shows the benefits of the proposed method. The latter has also been applied to 2016 National Health Interview Survey data.
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