Accounting for Complex Sampling in Survey Estimation: A Review of Current Software Tools

West Brady T. (), Sakshaug Joseph W. () and Aurelien Guy Alain S. ()
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West Brady T.: Survey Research Center, University of Michigan-Ann Arbor, 4118 Institute for Social Research, 426 Thompson Street, Ann Arbor, MI, 48106, U.S.A.
Sakshaug Joseph W.: Institute for Employment Research, Regensburger Strasse 104, Nuremberg, 90478, Germany.
Aurelien Guy Alain S.: Walter R. McDonald & Associates, 12300 Twinbrook Pkwy, Suite 310, Rockville, MD 20852, U.S.A.

Journal of Official Statistics, 2018, vol. 34, issue 3, 721-752

Abstract: In this article, we review current state-of-the art software enabling statisticians to apply design-based, model-based, and so-called “hybrid” approaches to the analysis of complex sample survey data. We present brief overviews of the similarities and differences between these alternative approaches, and then focus on software tools that are presently available for implementing each approach. We conclude with a summary of directions for future software development in this area.

Keywords: Complex sample survey data; statistical software; design-based analysis; model-based analysis; multilevel modeling (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:34:y:2018:i:3:p:721-752:n:7

DOI: 10.2478/jos-2018-0034

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