htzvara (?) wrote:
i have one variable which represents if the patient has the disease (coding: 0-
1)--and this is standard.
Additionally i have 12 more variables which represents the outcome of 12
different diagnostic procedures (coding: 0-1 for all of them).I want to find
which is the best diagnostic procedure. I calculate the sensitivity and
specificity and their confidence intervals for each of them. If the confidence
interval for the sensitivity of one diagnostic procedure do not overlap the
confidence interval for the Se of another diagnostic procedure then the
difference is significant.
Is there any test to perform and give p_value? Is there a need to make a
correction for multiple comparisons.?
----
It is not quite clear to me what you want. If it is to find the single test that has the "best" predictive value, try Paul Seed's -diagt- (findit diagt). However, you must look at both sensitivity and specificity to get a meaningful assessment.
I am not sure why you want to test whether the sensitivity of two tests are significantly different. And the confidence interval comparison you describe is quite insensititive.
Would this show what you need:
Make a logistic regression followed by -lroc- (ROC analysis):
. logistic disease test1-test12
. lroc
You might then try to remove tests to see whether removal makes a difference to the AUC (area under curve).
Hope this helps
Svend
________________________________________________________
Svend Juul
Institut for Folkesundhed, Afdeling for Epidemiologi
(Institute of Public Health, Department of Epidemiology)
Vennelyst Boulevard 6
DK-8000 Aarhus C, Denmark
Phone, work: +45 8942 6090
Phone, home: +45 8693 7796
Fax: +45 8613 1580
E-mail: [email protected]
_________________________________________________________
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