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Re: st: comparison of diagnostic procedures


From   htzavara@med.uoa.gr
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: comparison of diagnostic procedures
Date   Thu, 8 Sep 2005 16:15:47 +0300

&Agr;&rgr;&khgr;&igr;&kgr;&oacgr; &mgr;&eeacgr;&ngr;&ugr;&mgr;&agr; &agr;&pgr;&oacgr;  Roger Harbord <roger.harbord@bristol.ac.uk>:

thank you a lot for your help. This is the solution and i have already find it 
in a related article. I would like to ask you if you know how i will produce 
an error graph (graph of sensitivities and their confidence interval) for 
every diagnostic test? Does stata 8 support a graph like this?

thank you a lot in advance!!!!!!





> As Pepe mentions on p43, you can test the null hypothesis of equal 
> sensitivity or  of equal specificity of two binary tests done on the same 
> people using McNemar's test (-symmetry- or -mcc- commands in Stata). I 
> think something like:
> 
> . symmetry test1 test2 if disease==1   /* for sensitivity */
> . symmetry test1 test2 if disease==0   /* for specificity */
> 
> 
> However with 12 tests there are a lot of comparisons (66 for each of sens & 
> spec) so some allowance for multiple testing does seem a good idea.
> 
> A Bayesian approach seems quite attractive for this sort of problem as you 
> can then meaningfully ask "what is the probability that test X has the 
> highest sensitivity?", which you can't in a frequentist framework. You'd 
> need to switch to something like WinBUGS to get an answer to that though.
> 
> If one test has higher sensitivity than another but lower specificity or 
> vice-versa then which is better also depends on the disbenefits of false 
> positives compared to false negatives of course.
> 
> Roger.
> 
> -- 
> Roger Harbord                             roger.harbord@bristol.ac.uk
> MRC Health Services Research Collaboration & Dept. of Social Medicine
> University of Bristol        http://www.epi.bris.ac.uk/staff/rharbord
> 
> --On 07 September 2005 15:07 -0400 "Michael P. Mueller" 
> <michael.mueller@utoronto.ca> wrote:
> 
> > You might want to take a look at this book: Pepe, M.S. (2003).
> > Statistical Evaluation of Medical Tests for Classification and
> > Prediction. Dr. Pepe has Stata programs on her webpage you can download.
> > Hope this helps,
> > Michael
> >
> > htzavara@med.uoa.gr wrote:
> >
> >> &Agr;&rgr;&khgr;&igr;&kgr;&oacgr; &mgr;&eeacgr;&ngr;&ugr;&mgr;&agr; &agr;&pgr;&oacgr;  Svend Juul <SJ@SOCI.AU.DK>:
> >>
> >>
> >>
> >>> 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
> >>>
> >>>
> >>> Thank you very much for your help.
> >>>
> >>>
> >> I know about diagt and i used it to obtain the sensitivity - specificity.
> >> Roc analysis cannot help as the variables which represents the
> >> diagnostic  tests are not continuous but dichotomous (0-1).Even if i can
> >> see, which test  has the best se-sp i want to perform a test to prove it.
> >>
> >> thank you again.
> >>
> 
> 
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