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.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
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
(with abstract),
plain text
(with abstract),
BibTeX,
RIS (EndNote, RefMan, ProCite),
ReDIF
Did you know? You can create a compilation of all publications of a group of people, say alumni of a program, your students or memers of an association.