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A closer examination of subpopulation analysis of complex-sample survey data


  • Brady T. West

    () (Center for Statistical Consultation and Research, University of Michigan)

  • Patricia Berglund

    () (Institute for Social Research, University of Michigan)

  • Steven G. Heeringa

    () (Institute for Social Research, University of Michigan)


In recent years, general-purpose statistical software packages have incorporated new procedures that feature several useful options for design-based analysis of complex-sample survey data. A common and frequently desired technique for analysis of survey data in practice is the restriction of estimation to a subpopulation of interest. These subpopulations are often referred to interchangeably in a variety of fields as subclasses, subgroups, and domains. In this article, we consider two approaches that analysts of complex-sample survey data can follow when analyzing subpopulations; we also consider the implications of each approach for estimation and inference. We then present examples of both approaches, using selected procedures in Stata to analyze data from the National Hospital Ambulatory Medical Care Survey (NHAMCS). We conclude with important considerations for subpopulation analyses and a summary of suggestions for practice. Copyright 2008 by StataCorp LP.

Suggested Citation

  • Brady T. West & Patricia Berglund & Steven G. Heeringa, 2008. "A closer examination of subpopulation analysis of complex-sample survey data," Stata Journal, StataCorp LP, vol. 8(4), pages 520-531, December.
  • Handle: RePEc:tsj:stataj:v:8:y:2008:i:4:p:520-531

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    References listed on IDEAS

    1. Horton, Nicholas J. & Kleinman, Ken P., 2007. "Much Ado About Nothing: A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models," The American Statistician, American Statistical Association, vol. 61, pages 79-90, February.
    2. Frauke Kreuter & Richard Valliant, 2007. "A survey on survey statistics: What is done and can be done in Stata," Stata Journal, StataCorp LP, vol. 7(1), pages 1-21, February.
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    Cited by:

    1. Stanislav Kolenikov, 2010. "Resampling variance estimation for complex survey data," Stata Journal, StataCorp LP, vol. 10(2), pages 165-199, June.
    2. Walsh, John P. & Lee, You-Na, 2015. "The bureaucratization of science," Research Policy, Elsevier, vol. 44(8), pages 1584-1600.
    3. Lee, You-Na & Walsh, John P. & Wang, Jian, 2015. "Creativity in scientific teams: Unpacking novelty and impact," Research Policy, Elsevier, vol. 44(3), pages 684-697.


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