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From |
Lee Sieswerda <Lee.Sieswerda@tbdhu.com> |

To |
"'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: False negatives in clinical work |

Date |
Tue, 18 Feb 2003 19:56:07 -0500 |

Usually, if one wants to compare two diagnostic tests against a gold standard, one is interested in both the false positive and false negative rates. One of the methods for comparing diagnostic tests with a gold standard is ROC analysis (see -help roc-). ROC analysis helps one to find the optimum balance of sensitivity and specificity. However, according to the information you've provided, your friend's study appears to only consist of true positives, so apparently he is not interested in the false positive rate or the specificity. If this is so, it will not be amenable to ROC analysis. If he is truly interested only in the false negatives, then all you really need to do is compare the proportion of false negatives in test A with the proportion of false negatives in test B. You can play around recoding the Low, Medium, and High ratings and compare the proportion of false negatives among the various recodes. With only 15 cases, and no apparent concern for false positives, and with no other information about the diagnostic tests other than you've given, it should not be too difficult to eye-ball which recode would yield zero false negatives, in which case you really don't need statistical analysis, right?.... :-) I'm kidding, of course, but I say it to point out that there isn't much point in doing a statistical analysis if you only have true positives in the study and you can recode the ratings anyway you want. Kidding aside, my guess is that your friend is interested in the optimum balance between sensitivity and specificity, and that he has some non-cases in the study. ROC analysis is probably what you want here, and the manual has a good explanation and references. There is also -diagt- on SSC. Regards, Lee Lee Sieswerda, Epidemiologist Thunder Bay District Health Unit 999 Balmoral Street Thunder Bay, Ontario Canada P7B 6E7 Tel: +1 (807) 625-5957 Fax: +1 (807) 623-2369 Lee.Sieswerda@tbdhu.com www.tbdhu.com > -----Original Message----- > From: TDietzVT@aol.com [SMTP:TDietzVT@aol.com] > Sent: Tuesday, February 18, 2003 11:41 AM > To: statalist@hsphsun2.harvard.edu > Subject: st: False negatives in clinical work > > I'm trying to help a pathologist friend with a study and am not sure how > to > proceed. She has 15 cases that are positive for a disease. There are two > > standard methods for diagnosing the disease from tissue samples, say A and > B. > A and B each produce a rating of High, Medium or Low on the indicator > used > for diagnosis. Each case has been rated by each method. She would like > to > know if there is a statistically significant difference in the number of > false negatives between the two methods. It would also be useful to know > if > collapsing, for example, High and Medium into one category yields a lower > false negative rate. > Any suggestions on how to proceed most welcome. > Best, > Tom Dietz > > > > Professor of Sociology and Crop and Soil Sciences > Acting Director of the Environmental Science and Policy Program > Acting Associate Dean for Environmental Science and Policy, College of > Agriculture and Natural Resources, College of Natural Science, College of > Social Science > Michigan State University > Off campus phone: 802-372-4389 > Off campus fax: 802-372-4389 > Email: tdietzvt@aol.com > Office: 118 Linton > On campus phone: 517-355-0302 > On campus fax: 517-353-3355 > * > * 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/

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