Publication Type

Journal Article

Version

submittedVersion

Publication Date

3-2020

Abstract

Non-response is a commonly encountered problem in many population-based surveys. Broadly speaking, non-response can be due to refusal or failure to contact the sample units. Although both types of non-response may lead to bias, there is much evidence to indicate that it is much easier to reduce the proportion of non-contacts than to do the same with refusals. In this article, we use data collected from a nationally representative survey under the Demographic and Health Surveys program to study non-response due to refusals to HIV testing in Malawi. We review existing estimation methods and propose novel approaches to the estimation of HIV prevalence that adjust for refusal behaviour. We then explain the data requirement and practical implications of the conventional and proposed approaches. Finally, we provide some general recommendations for handling non-response due to refusals and we highlight the challenges in working with Demographic and Health Surveys and explore different approaches to statistical estimation in the presence of refusals. Our results show that variation in the estimated HIV prevalence across different estimators is due largely to those who already know their HIV test results. In the case of Malawi, variations in the prevalence estimates due to refusals for women are larger than those for men.

Keywords

Bias, Demographic and Health Surveys, missing data, non-response, refusals, Malawi

Discipline

Health Economics

Research Areas

Applied Microeconomics

Publication

Statistical Methods in Medical Research

Volume

29

Issue

3

First Page

811

Last Page

826

ISSN

0962-2802

Identifier

10.1177/0962280219844536

Publisher

SAGE Publications (UK and US)

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1177/0962280219844536

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