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Re: st: comparing differences in Kendall's tau or Spearman's coefficient using somersd

From   Roger Newson <>
To   "" <>
Subject   Re: st: comparing differences in Kendall's tau or Spearman's coefficient using somersd
Date   Mon, 26 Apr 2010 11:08:34 +0100

As I understand it, you are trying to measure the tau-a correlation between "Efficiency definition 1" (ED1) in Year A and ED1 in Year B, and then measure the tau-a correlation between "Efficiency Definition 2" (ED2) in Year A and ED2 in Year B, and then calculate a confidence interval for the difference between the 2 taus.

The somersd package unfortunately does not yet do this, The examples in the manual are more similar to the case where there is a third efficiency definition (ED3), which is thought too be a "gold standard". We would then compare the tau-a between ED3 and ED1 with the tau-a between ED3 and ED2, and find out which is greater.

To do what you want to do, the best answer will be to use either the jackknife or the bootstrap. Both of these are available in Stata. However, your query has drawn attention to an important limitation of the -somersd- package. It would be an improvement if -somersd- could output the delta-jackknife pseudovalues or the delta-jackknife influence function to an output dataset (or resultsset) with 1 observation per cluster and data on the pseudovalues or influence function. This is one of many improvements I would like to make to -somersd- when I have the time.

I hope this helps.

Best wishes


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 25/04/2010 19:11, Chong, Qi Lin Andrew wrote:
The scores are bounded from 1 to infinity, and a half-normal
distribution has been assumed for them in the original stochastic
frontier (and a normal distribution for the errors). A score of say
1.25 indicates a firm incurs 25% more costs than the most efficient
firm it can be compared
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