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Activity Number: 27 - Innovative Methods for Missing Data and Measurement Error in Health Research
Type: Topic Contributed
Date/Time: Monday, August 3, 2020 : 10:00 AM to 11:50 AM
Sponsor: Health Policy Statistics Section
Abstract #312485
Title: Multiple Imputation for Nonignorable Item Nonresponse in Complex Surveys Using Auxiliary Margins
Author(s): Olanrewaju Akande* and Jerry Reiter
Companies: Duke University and Duke University
Keywords: Auxiliary; Complex; Missing; Nonignorable; Survey; Weight

We outline a framework for multiple imputation of nonignorable item nonresponse when the marginal distributions of some of the variables with missing values are known. In particular, our framework ensures that (i) the completed datasets result in design-based estimates of totals that are plausible, given the margins, and (ii) the completed datasets maintain associations across variables as posited in the imputation models. To do so, we propose an additive nonignorable model for nonresponse, coupled with a rejection sampling step. The rejection sampling step favors completed datasets that result in design-based estimates that are plausible given the known margins. We illustrate the framework using simulations with stratified sampling.

Authors who are presenting talks have a * after their name.

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