A doubly robust method to handle missing multilevel outcome data with application to the China Health and Nutrition Survey

Volume: 41, Issue: 4, Pages: 769 - 785
Published: Nov 16, 2021
Abstract
Missing data are common in longitudinal cohort studies and can lead to bias, particularly in studies with informative missingness. Many common methods for handling informatively missing data in survey samples require correctly specifying a model for missingness. Although doubly robust methods exist to provide unbiased regression coefficients in the presence of missing outcome data, these methods do not account for correlation due to clustering...
Paper Details
Title
A doubly robust method to handle missing multilevel outcome data with application to the China Health and Nutrition Survey
Published Date
Nov 16, 2021
Volume
41
Issue
4
Pages
769 - 785
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