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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. > >> > > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: comparison of diagnostic procedures***From:*Roger Harbord <roger.harbord@bristol.ac.uk>

**References**:**Re: st: comparison of diagnostic procedures***From:*"Michael P. Mueller" <michael.mueller@utoronto.ca>

**Re: st: comparison of diagnostic procedures***From:*Roger Harbord <roger.harbord@bristol.ac.uk>

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