Reducing Attrition in Phone-based Panel Surveys: A Web Application to Facilitate Best Practices and Semi-Automate Survey Workflow

Ala Alrababah, Marine Casalis, Daniel Masterson, Dominik Hangartner, Wehrli, and Jeremy Weinstein
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Daniel Masterson: University of California, Santa Barbara
Wehrli,: ETH Zürich

No gyz3h, OSF Preprints from Center for Open Science

Abstract: Panel surveys and phone-based data collection are essential tools for survey research and are often used together due to the practical advantages of conducting repeated interviews over the phone. These tools are particularly critical for research in dynamic or high-risk settings, as highlighted by researchers' responses to the COVID-19 crisis. However, maintaining low attrition is a major problem with panel surveys. Current solutions focus on statistical fixes to address attrition ex post but often overlook a preferable solution: minimizing attrition in the first place. Building on a review of political science panel studies and a systematic overview of best practices, we propose a framework for reducing attrition and present an online platform to facilitate the logistics of survey implementation. The web application semi-automates scheduling survey calls and enumerator workflows, which helps reduce panel attrition while also increasing data quality and minimizing enumerator errors. Applying the proposed framework to a panel study of Syrian refugees in Lebanon, we are able to maintain participant retention at 67% around three and a half years after the baseline survey. We conclude by offering guidelines for transparently reporting panel studies and comprehensively describing their designs.

Date: 2023-11-03
New Economics Papers: this item is included in nep-ara
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:gyz3h

DOI: 10.31219/osf.io/gyz3h

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