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From |
htzavara@med.uoa.gr |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: comparison of diagnostic procedures |

Date |
Sat, 10 Sep 2005 21:20:37 +0300 |

&Agr;&rgr;&khgr;&igr;&kgr;&oacgr; &mgr;&eeacgr;&ngr;&ugr;&mgr;&agr; &agr;&pgr;&oacgr; Roger Harbord <roger.harbord@bristol.ac.uk>: 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 htzavara@med.uoa.gr wrote: > > > &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 Newson <roger.newson@kcl.ac.uk>

**References**:**Re: st: comparison of diagnostic procedures***From:*htzavara@med.uoa.gr

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

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