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)
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. Copyright 2008 by StataCorp LP.
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Article provided by StataCorp LP in its journal Stata Journal.
Volume (Year): 8 (2008) Issue (Month): 4 (December) Pages: 520-531 Download reference. The following formats are available: HTML
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