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Re: st: nonparametric regression with sampling weights

From   "Newson, Roger B" <>
To   "" <>
Subject   Re: st: nonparametric regression with sampling weights
Date   Thu, 18 Feb 2010 14:38:02 +0000

I don't know what questions you intend to answer. However, a rank stats package that allows sampling probability weights is the -somersd- package, downloadable from SSC.

The -somersd- package estimates a wide range of rank statistics, which are versions of Kendall's tau-a, Somers' D, or Theil-Sen median slopes, allowing the possibility of sampling probability weights and/or restriction to comparisons within strata. Apart from the .pdf manuals distributed with -somersd-, there are 3 Stata Journal references referred to in the on-line help, which can be downloaded from

There is also an example presented at a Stata User Meeting (Newson, 2006), which can be downloaded from

I hope this helps. BEst wishes



Newson R. 2006. On the central role of Somers’ D. Presented at the 12th UK Stata Users’ Group Meeting on 11-12 September, 2006.
Download from

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
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Web page:
Departmental Web page:

On 17/02/2010 21:18, Andaleeb Alam wrote:

I am working with Pakistan Standard Living Measurement Survey (it's a
household level survey with a two-stage stratified sample design). I am
interested in running a kernel weighted linear regression. From what I have
tried, Stata does not allow the use of analytic weights if I am using
svy:reg. What do you recommend I should do? Transform my data by my kernel
weights and then do svy:reg? I have come across papers that do non
parametric estimations using survey data so I am assumig that there must be
some stata command that lets you do this?! If there is no such Stata command
or my suggestion to transforms the data is incorrect, please recommend what
can I do?



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