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The Stata Journal
Volume 8 Number 4: pp. 520-531



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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, Ann Arbor
Ann Arbor, MI
bwest@umich.edu
Patricia Berglund
Institute for Social Research
University of Michigan, Ann Arbor
Ann Arbor, MI
pberg@umich.edu
Steven G. Heeringa
Institute for Social Research
University of Michigan, Ann Arbor
Ann Arbor, MI
sheering@umich.edu
Abstract.   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.
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View all articles with these keywords: survey data analysis, statistical software, complex sample designs, subpopulation analysis

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