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st: why don't confidence intervals from -proportion- use the same formula as -ci-?


From   Ronan Conroy <rconroy@rcsi.ie>
To   statalist edu <statalist@hsphsun2.harvard.edu>
Subject   st: why don't confidence intervals from -proportion- use the same formula as -ci-?
Date   Fri, 11 Jan 2013 11:44:42 +0000

I have a real problem with the confidence intervals produced by the -proportion- command. 

. input outcome freq

       outcome       freq
  1. 0 21
  2. 1 2
  3. end


Here is the confidence interval which is most probably closest the the nominal coverage according to 
- Brown L, Cai T, DasGupta A. Interval estimation for a binomial proportion. Statistical Science. 2001;16(2):101–17. 

. ci outcome [fw=freq], bin wil

                                                         ------ Wilson ------
    Variable |        Obs        Mean    Std. Err.       [95% Conf. Interval]
-------------+---------------------------------------------------------------
     outcome |         23    .0869565    .0587534          .02418    .2679598



Now here is what -proportion- does. 


. proportion outcome [fw=freq]

Proportion estimation               Number of obs    =      23

--------------------------------------------------------------
             | Proportion   Std. Err.     [95% Conf. Interval]
-------------+------------------------------------------------
outcome      |
           0 |   .9130435   .0600739      .7884579    1.037629
           1 |   .0869565   .0600739      -.037629    .2115421
--------------------------------------------------------------

. 
end of do-file

According to the manual:


"Methods and formulas
proportion is implemented as an ado-file.
Proportions are means of indicator variables; see [R] mean."

Is anyone prepared to defend this approach as the only formula implemented by -proportion-? Or indeed to tell me that they have managed to publish a paper that included confidence intervals such as the one above?


I myself find this bizarre. Consider the example above. The confidence interval includes a value that is impossible - zero. With two observed successes, the success rate cannot be zero. And it includes probabilities that have no definition: negative probabilities. While I am prepared to accept that physicists have now produced temperatures that are lower than absolute zero, I cannot bring myself to persuade anyone that a confidence interval for a probability can extend beyond the interval 0-1.


I believe it would be good if Stata's -proportion- command allowed the choice of some more believable methods. 



Ronán Conroy
rconroy@rcsi.ie
Associate Professor
Division of Population Health Sciences
Royal College of Surgeons in Ireland
Beaux Lane House
Dublin 2


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