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Re: st: Caterpillar Plot


From   Ronan Conroy <[email protected]>
To   "[email protected]" <[email protected]>
Subject   Re: st: Caterpillar Plot
Date   Fri, 11 Mar 2011 11:34:51 +0000

On 10 Mar 2011, at 22:34, Elizabeth Sanders wrote:

> Can someone tell me how to make a caterpillar plot in Stata? I can't find instructions anywhere, but I know it must be possible.


-ciplot- would seem to do the job, but note this reference, which seems to suggest that there are better alternatives. The example that they discuss concerns plotting hospital mortality rates and their confidence intervals.

http://ats.ctsnetjournals.org/cgi/content/full/86/1/348

To quote the authors:

The purpose of this plot is to identify where differences in performance between hospitals may be explicable by chance. Although this type of plot, colloquially known as the caterpillar plot, is widely used in performance monitoring, there are some important conceptual issues that make the use of such plots problematic:

1 A separate interval of uncertainty is drawn for each hospital. If any interval excludes the null (ie, risk ratio = 1), then this suggests evidence against the null hypothesis: that all differences between the units are explicable by chance. Therefore, six significance tests are undertaken to address a single underlying hypothesis. Thus, there is misalignment between the plot and the hypothesis of interest. 

2 The plot does not address multiple-testing, rather it encourages six comparisons of hospitals with the expected rate (and 15 comparisons between hospitals). As more hospitals are included, it is expected that one or more units will have a 95% confidence interval that does not include the null simplydue to chance. 

3 The plot encourages an erroneous interpretation that if the confidence intervals of one unit overlap with those of another, then those units are similar to each other [2].
 
4 The sample sizes are not directly shown (although the relative sizes of the confidence intervals give some indication of difference in sample size). 

5 Ordering the plot from low to high mortality encourages spurious ranking of hospitals, which has been shown to be unreliable, as it mainly reflects the play of chance and not real differences

Ronán Conroy
[email protected]
Associate Professor
Division of Population Health Sciences
Royal College of Surgeons in Ireland
Beaux Lane House
Dublin 2


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