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From |
"Newson, Roger B" <r.newson@imperial.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: Non-parametric tests for survey data? (e.g., Kruskal-Wallace) |

Date |
Wed, 11 Feb 2009 10:50:09 -0000 |

One possibility might be to use the -somersd- package, downloadable from SSC using the -ssc- command in Stata. The -somersd- package generates confidence intervals for a wide range of rank statistics (particularly Somers' D and Kendall's tau-a), and can be used with sampling-probability weights (pweights) and/or the -svy:- prefix. It comes with 3 .pdf manuals, which you can get when you download the package. I hope this helps. Best wishes Roger Roger B Newson BSc MSc DPhil Lecturer in Medical Statistics Respiratory Epidemiology and Public Health Group National Heart and Lung Institute Imperial College London Royal Brompton Campus Room 33, Emmanuel Kaye Building 1B Manresa Road London SW3 6LR UNITED KINGDOM Tel: +44 (0)20 7352 8121 ext 3381 Fax: +44 (0)20 7351 8322 Email: r.newson@imperial.ac.uk Web page: http://www.imperial.ac.uk/nhli/r.newson/ Departmental Web page: http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/pop genetics/reph/ Opinions expressed are those of the author, not of the institution. -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Michael I. Lichter Sent: 10 February 2009 21:25 To: statalist@hsphsun2.harvard.edu Subject: st: Non-parametric tests for survey data? (e.g., Kruskal-Wallace) I don't see any procedures for doing non-parametric tests (aside from chi-square in svy: tab) with complex survey data (stratified, unequal probabilities of selection). I am particularly looking for tests of difference in ordinal dependent variables across k groups (k > 2). Kruskall-Wallace is the most obvious test, but only available for non-survey data. I assume that these procedures are not available because (a) it's not clear what to do with weights in nonparametric analyses anyway (which I infer partly from the fact that none of Stata's nonparametric procedures take weights), (b) because there's no theory about whether/how they should work, and/or (c) because nobody has gotten around to it yet. I'm looking for suggestions. One possibility that comes to mind is to generate ranks using -egen- and analyze using -svy: mean- or -svy: reg- (I'd use one-way ANOVA if somebody could explain how to do it with -svy- commands). I could also do -svy: intreg- for the variables that represent ranges underlying continuous variables (since most of my ordinal variables do represent well-defined but unequal-sized ranges of underlying continuous variables, e.g., 1 = "> 1", 2 = "2-4" 3 = "5 or more"), but that would require -intreg- to be robust to floor effects, and I doubt that it is (since the method assumes an underlying Normal distribution). (I guess -mlogit-, -ologit- and -gologit2- are also possibilities.) Thanks. -- Michael I. Lichter, Ph.D. Research Assistant Professor & NRSA Fellow UB Department of Family Medicine / Primary Care Research Institute UB Clinical Center, 462 Grider Street, Buffalo, NY 14215 Office: CC 125 / Phone: 716-898-4751 / E-Mail: mlichter@buffalo.edu * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: RE: Non-parametric tests for survey data? (e.g., Kruskal-Wallace)***From:*"Michael I. Lichter" <mlichter@buffalo.edu>

**References**:**st: Non-parametric tests for survey data? (e.g., Kruskal-Wallace)***From:*"Michael I. Lichter" <mlichter@buffalo.edu>

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