Confidence Interval for Sensitivity and Specificity

[Senema John]

I have the following data and would like to calculate the confidence interval for the sensitivity and specificity.
I used the tab command and col option to get the sensitivity and specificity but I will need the CI also.
Can anyone help?
The reference test is scores and the other test is f145.
Thanks
----------------------- copy starting from the next line -----------------------

* Example generated by -dataex-. To install: ssc install dataex
clear
input byte scores str7 f145
0 "0"
0 "0"
0 "0"
1 "1"
0 "0"
0 "0"
0 "0"
0 "0"
0 "1"
0 "0"
0 "0"
end

------------------ copy up to and including the previous line ------------------

Listed 11 out of 114 observations

[Felix Bittmann]

I found this here: https://www.stata.com/statalist/arch.../msg00779.html
If this ado does not help you one could also think about bootstrapping.

[daniel klein]

diagt (SSC) will provide what you seek (and more):

clear
input byte scores str7 f145
0 "0"
0 "0"
0 "0"
1 "1"
0 "0"
0 "0"
0 "0"
0 "0"
0 "1"
0 "0"
0 "0"
end

// we need numeric variables
destring f145 , generate(testvar)

diagt score testvar

yields

. diagt score testvar

           |        testvar
    scores |      Pos.       Neg. |     Total
-----------+----------------------+----------
  Abnormal |         1          0 |         1 
    Normal |         1          9 |        10 
-----------+----------------------+----------
     Total |         2          9 |        11 
True abnormal diagnosis defined as scores = 1


                                                  [95% Confidence Interval]
---------------------------------------------------------------------------
Prevalence                         Pr(A)      9.1%      0.2%      41.3%
---------------------------------------------------------------------------
Sensitivity                      Pr(+|A)    100.0%      2.5%    100.0%
Specificity                      Pr(-|N)     90.0%     55.5%     99.7%
ROC area               (Sens. + Spec.)/2      0.95         .      1.00 
---------------------------------------------------------------------------
Likelihood ratio (+)     Pr(+|A)/Pr(+|N)     10.00      1.56     64.20 
Likelihood ratio (-)     Pr(-|A)/Pr(-|N)      0.00         .         . 
Odds ratio                   LR(+)/LR(-)         .      0.00         . 
Positive predictive value        Pr(A|+)     50.0%      1.3%     98.7% 
Negative predictive value        Pr(N|-)    100.0%     66.4%    100.0% 
---------------------------------------------------------------------------

  Missing values or confidence intervals may be estimated
  using the -sf- or -sf0- options.

Also, see

help ci

[Senema John]

Thanks a lot Daniel Klein.

This was very helpful. So happy with the information. Just solved my problem!!!!!

Thanks again.