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

["Michael I. Lichter" <mlichter@buffalo.edu>]

Thank you Nick and Stas for clarifying the reasons behind the lack of 
nonparametric procedures for complex survey data.

Thank you Roger for suggesting Somers' D. What I glean from the 
documentation suggests that the X variable in -somersd- can be 
dichotomous or it can be at least ordinal, but it cannot be nominal with 
k > 2 categories. For my (4-category nominal) situation, I would need to 
do multiple tests, possibly with a Bonferroni adjustment. That sounds 
doable.

Stas, I'd be interested on your take on the application of Somer's D to 
complex survey data. -somersd- allows jackknifed errors, which should 
relax the assumption of independence, and the statistics is supposed to 
be robust to distributional differences, and has a well-defined 
population expectation.

Roger, FWIW, the help page for somersd says that your dissertation was 
completed in 1887, and " {help lincom]" should, I guess, be "{help lincom}".

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 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

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