A closer examination of subpopulation analysis of complex-sample survey data
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.
Volume (Year): 8 (2008)
Issue (Month): 4 (December)
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- 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.
- 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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