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Article type: Research Article
Authors: Parker, Jennifer* | Miller, Kristen | He, Yulei | Scanlon, Paul | Cai, Bill | Shin, Hee-Choon | Parsons, Van | Irimata, Katherine
Affiliations: Division of Research and Methodology, National Center for Health Statistics, Hyattsville, MD, 20782, USA
Correspondence: [*] Corresponding author: Jennifer Parker, Division of Research and Methodology, National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, #4650, Hyattsville, MD, 20782, USA. Tel.: +1 301 458 4419; E-mail: [email protected].
Note: [1] The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the National Center for Health Statistics, Centers for Disease Control and Prevention.
Abstract: The National Center for Health Statistics is assessing the usefulness of recruited web panels in multiple research areas. One research area examines the use of close-ended probe questions and split-panel experiments for evaluating question-response patterns. Another research area is the development of statistical methodology to leverage the strength of national survey data to evaluate, and possibly improve, health estimates from recruited panels. Recruited web panels, with their lower cost and faster production cycle, in combination with established population health surveys, may be useful for some purposes for statistical agencies. Our initial results indicate that web survey data from a recruited panel can be used for question evaluation studies without affecting other survey content. However, the success of these data to provide estimates that align with those from large national surveys will depend on many factors, including further understanding of design features of the recruited panel (e.g. coverage and mode effects), the statistical methods and covariates used to obtain the original and adjusted weights, and the health outcomes of interest.
Keywords: Web survey, measurement error, propensity-score adjustment, recruited panel
DOI: 10.3233/SJI-200678
Journal: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1199-1211, 2020
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