Publication Type

Working Paper

Version

publishedVersion

Publication Date

2-2019

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 dierent approaches to statistical estimation in the presence of refusals. Our results show that variation in the estimated HIV prevalence across dierent 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

Econometrics | Health Economics

Research Areas

Econometrics; Applied Microeconomics

Volume

06-2019

First Page

1

Last Page

26

Publisher

SMU Economics and Statistics Working Paper Series, Paper No. 06-2019

City or Country

Singapore

Copyright Owner and License

Authors

Comments

Published in Statistical Methods in Medical Research, 2019 May, https://doi.org/10.1177/0962280219844536

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