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From |
Roger Newson <roger.newson@kcl.ac.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Interobserver agreement for continuous variables |

Date |
Fri, 18 Oct 2002 12:26:40 +0100 |

At 21:43 17/10/02 -0700, Nitin wrote:

I personally would use a variation on the intra-class Kendall's tau-a, which can be calculated (with confidence limits) using my -somersd- package, downloadable from SSC. (Type -ssc describe somersd- or -net search somersd- within Stata to find how to download.) First, create a data set with 1 obs for every ordered pair of measurements on the same subject by different observers. Such a data set might have variables as follows:Hi Nick and Scott, Thank you for the response. But the concord and other tests contained in it are only for 2 observers/raters. I am looking for something that calculates interobserver agreement for a continuous variable WHEN THERE ARE MORE THAN 3 RATERS AND THE number of raters vary for each subject ? I look forward to hearing from you. Nitin

subjid Subject ID

obsid1 First observer ID

obsid2 Second observer ID

y1 First observer rating

y2 Second observer rating

Such a data set might be created using the -joinby- package. Note that each combination of Observer A, Observer B and Patient X should appear twice in this data set, once with Observer A as first observer and Observer B as second observer, and once with Observer B as first observer and Observer A as second observer. Once you have created this data set, type

somersd y1 y2,taua tdist cluster(subjid)

and Stata will calculate confidence limits for a Kendall tau-a between -y1- and -y2-, clustered by -subjid-. This tau-a is a difference between 2 probabilities, namely the probability of concordance (two raters order two subjects in the same way) and the probability of discordance (two raters order two subjects in the opposite way). For instance, if Kendall's tau-a is 0.70, then this means that, if 2 observers are given 2 randomly chosen subjects and asked which one to rate more highly, then the observers are 70% more likely to agree than to disagree.

For more information on Kendall's tau-a, a possible reference is Newson (2002), which in turn has many more references.

I hope this helps.

Roger

References

Newson R. Parameters behind "non-parametric" statistics: Kendall's tau, Somers' D and median differences. The Stata Journal 2002; 2(1): 45-64.

--

Roger Newson

Lecturer in Medical Statistics

Department of Public Health Sciences

King's College London

5th Floor, Capital House

42 Weston Street

London SE1 3QD

United Kingdom

Tel: 020 7848 6648 International +44 20 7848 6648

Fax: 020 7848 6620 International +44 20 7848 6620

or 020 7848 6605 International +44 20 7848 6605

Email: roger.newson@kcl.ac.uk

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

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**References**:**st: RE: Interobserver agreement for continuous variables***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: RE: Interobserver agreement for continuous variables***From:*Nitin Jain <drnitinjain@yahoo.com>

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