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Re: st: Non-parametric test equivalents with survey-weighted data


From   Roger Newson <r.newson@imperial.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Non-parametric test equivalents with survey-weighted data
Date   Sat, 06 Aug 2011 18:51:45 +0100

The -somersd- package can be downloaded from SSC, and can be used to do rank statistics for clustered and/or sampling-probability weighted data. There is also a package -scsomersd- which calls the -somersd- package to do scenario comparisons in rank statistics. Both of these packages produce confidence intervals, not just P-values. The on-line help for -somersd- contains references to papers on the subject, published in The Stata Journal.

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/popgenetics/reph/

Opinions expressed are those of the author, not of the institution.

On 05/08/2011 17:00, Janet Rosenbaum wrote:
Frequently I use kwallis, ranksum, or nptrend for testing between
groups, depending on the nature of the variables involved.  Stata
doen't support these tests in survey-weighted data.

Are there any equivalent tests to use when comparing weighted data?
Survey-weighted data can use Pearson's chi-square or Wald, but my
understanding is that neither is equivalent.

As background, the weights are inverse probability weights derived
from a propensity score model.  I have a cluster variable, but as far
as I know that doesn't matter with non-parametric tests anyhow.

Thanks for any thoughts,

Janet
Janet Rosenbaum, Ph.D.
Assistant Professor
University of Maryland, College Park.
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