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From |
"Michael I. Lichter" <mlichter@buffalo.edu> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 11 Feb 2009 13:13:19 -0500 |

Thanks. Michael Newson, Roger B wrote:

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 8322Email: r.newson@imperial.ac.ukWeb 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 fromchi-square in svy: tab) with complex survey data (stratified, unequalprobabilities of selection). I am particularly looking for tests ofdifference in ordinal dependent variables across k groups (k > 2).Kruskall-Wallace is the most obvious test, but only available fornon-survey data.I assume that these procedures are not available because (a) it's notclear what to do with weights in nonparametric analyses anyway (which Iinfer partly from the fact that none of Stata's nonparametric procedurestake weights), (b) because there's no theory about whether/how theyshould 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- andanalyze using -svy: mean- or -svy: reg- (I'd use one-way ANOVA ifsomebody could explain how to do it with -svy- commands). I could alsodo -svy: intreg- for the variables that represent ranges underlyingcontinuous variables (since most of my ordinal variables do representwell-defined but unequal-sized ranges of underlying continuousvariables, e.g., 1 = "> 1", 2 = "2-4" 3 = "5 or more"), but that wouldrequire -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/

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

**st: RE: Non-parametric tests for survey data? (e.g., Kruskal-Wallace)***From:*"Newson, Roger B" <r.newson@imperial.ac.uk>

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