You might possibly want to use the -senspec- package (downloadable from
SSC) to calculate sensitivities and specificities, and then calculate their
standard errors using the standard formulas.. A good overall performance
indicator for comparing two ROC curves is the ROC area, and the difference
between ROC areas (with confidence limits) can be calculated using the
-somersd- package (also downloadable from SSC) together with -lincom-.
I hope this helps.
Roger
At 19:20 10/09/2005, you wrote:
������ ������ ��� Roger Harbord <[email protected]>:
i tried to save the estimates with "parmest" but it is not possible
with "diagt". The graph options "serrbar" and "twoway rcap" can produce a
graph with the confidence intervals of the estimates but it is not
possible to
include the values of sensitivity or specificity.Any advice will be very
helpful.
Thank you a lot!
> Try -serrbar- or -twoway rcap-. However you'd need to first save the
> estimates and CIs as variables. Roger Newson's -parmest- package could be
> one way to do that, after which you could use his -eclplot- package (both
> available on SSC) as an alternative to -serrbar- or -twoway rcap-.
>
> Roger H.
>
> --On 08 September 2005 16:15 +0300 [email protected] wrote:
>
> > ������ ������ ��� Roger Harbord <[email protected]>:
> >
> > 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 [email protected]
> >> 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"
> >> <[email protected]> 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
> >> >
> >> > [email protected] wrote:
> >> >
> >> >> ������ ������ ��� Svend Juul <[email protected]>:
> >> >>
> >> >>
> >> >>
> >> >>> 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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>
--
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--
Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
Division of Asthma, Allergy and Lung Biology
King's College London
5th Floor, Capital House
42 Weston Street
London SE1 3QD
United Kingdom
Tel: 020 7848 6648 International +44 20 7848 6648
Fax: 020 7848 6620 International +44 20 7848 6620
or 020 7848 6605 International +44 20 7848 6605
Email: [email protected]
Website: http://phs.kcl.ac.uk/rogernewson/
Opinions expressed are those of the author, not the institution.
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