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Re: st: RE: New package -wridit- on SSC

From   "Roger B. Newson" <>
Subject   Re: st: RE: New package -wridit- on SSC
Date   Mon, 27 Feb 2012 12:56:21 +0000

Thanks to Nick for these references, which I will check out. Ridits seem to have nearly as many names as Somers' D, some of whose forms are asymptotically equivalent either to a paired t-test on the ridits or to an unequal-variance t-test on the ridits.


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:

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

On 27/02/2012 12:45, Nick Cox wrote:
Ridits are also the mid-distribution function of Parzen (1993, 3295) and the grade function of Haberman (1996, 240-241).

     Haberman, S. J. 1996.  Advanced Statistics Volume I: Description of Populations.  New York: Springer.

     Parzen, E. 1993. Change PP plot and continuous sample quantile function. Communications in Statistics -Theory and Methods 22: 3287-3304.


Roger B. Newson

Thanks as always to Kit Baum, a new package -wridit- is now available
for download from SSC. In Stata, use the -ssc- command to do this.

The -wridit- package is described as below on my website, and calculayes
weighted ridits for a variable. Zero weights are allowed, in which case
the ridits for the observations with zero weights are relative to the
weight distribution in the observations with non-zero weights. Ridits,
and the left, right and central inverse ridits, are important in rank
statistics, which, strictly speaking, are really ridit statistics. They
are also potentially useful in spline statistics, where the user might
want to define a spline in the ridit of an X-variable, instead of in the
X-variable itself.

I would like to thank Nick Cox for writing the -ridit()- function of the
-egenmore- package, which generates unweighted ridits, and from which I
borrowed a few ideas for -wridit-. I slightly revised the algorithm for
-wridit-, in order to avoid the small numerical accuracy issues
associated with adding a small probability to a large probability.

package wridit from

        wridit: Generate weighted ridits

        wridit inputs a variable and generates its weighted ridits.
        If no weights are provided, then all weights are assumed
        equal to 1, so unweighted ridits are generated.

        Author: Roger Newson
        Distribution-Date: 22february2012
        Stata-Version: 10

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