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From |
Richard_Lenhardt@rush.edu |

To |
statalist-digest@hsphsun2.harvard.edu |

Subject |
st: "adjusted" kappas |

Date |
Thu, 18 Aug 2005 17:23:51 -0500 |

t 01:50 PM 8/17/2005, Richard_Lenhardt@rush.edu wrote: Hello We submitted a manuscript comparing two observers measuring 10 dicotomous variables. We measured kappa, to assess concordance between observers. A reviewer asked that we calculate an overall value (composite) of the kappas, for all 10 variables. (Fleiss, Stat Methods for Rates and Proportions, 2nd or 3rd edition). I couldn't find such a function in stata (overall kappa). Would there be another way to calculate this other than by hand? Also, the study was completed at 5 different hospitals. The reviewer asked that we take into account hospital to hospital variation when calculating kappas. I wasn't aware that kappas could be adjusted for the 5 hospitals, other than generating a large matrix of kappas corresponding to the different hospitals. Would there be a way to take into account the variation in agreement among the hospitals when estimating the kappas? Thank you! Richard Lenhardt, MD, MPH Assistant Professor of Medicine Division of Pulmonary and Critical Care Medicine Rush University Medical Center Chicago, IL Hospital can be used as a stratification factor. You say you have 10 dichotomous variables that are being rated. This is what you can do. Take variable Y1 first. Compute stratum-specific kappas (for each hospital separately). Then, compute a weighted-average combined kappa. Whether that's reasonable depends on whether you are estimating the same kappa parameter in all the strata -- eyeballing and a homogeneity test might help here. In flavor, all this is like stratification and computation of an adjusted MH odds ratio. I don't have Fleiss in front of me but the specifics are in there. Then do the same thing for the rest of your variables, Y2, ..., Y10. You now have 10 "adjusted" kappas (controlling for hospital). Should you compute an overall adjusted kappa across all 10 ratings? Maybe yes, maybe no. Could you do it? In principle, you could use the same procedure to get a weighted kappa from all those 10 kappas. The trouble is that the individual kappas are correlated beyond the fact that you are using the same raters -- you are also probably using the same patients. I think the only feasible way to get a handle on such a beast is through the bootstrap. Hope this helps. CD The documents accompanying this transmission may contain confidential health or business information. This information is intended for the use of the individual or entity named above. If you have received this information in error, please notify the sender immediately and arrange for the return or destruction of these documents. ________________________________________________________________ Constantine Daskalakis, ScD Assistant Professor, Thomas Jefferson University, Division of Biostatistics, 211 S. 9th St., Suite 602, Philadelphia, PA 19107 Tel: 215-955-5695 Fax: 215-503-3804 Email: c_daskalakis@mail.jci.tju.edu Webpage: http://www.jefferson.edu/clinpharm/bio/ CD, Thank you for your help, now I understand what to do with stata. This brings me to a follow up question (for anyone): To calculate an "adjusted" kappa, based on 5 hospitals, according to Fleiss, one would sum the hospital kappas, weighted by the inverse of the square of the hospital kappa standard errors. adjusted kappa for given item = SUM kappahosp(i) / SUM 1/se(kappahosp(i))^2 se(kappahosp(i))^2 / I'm trying to write a do program that enables this with the following variables: Study ID HospID A1 B1 A2 B2 .... 1 1 Y Y Y N 2 1 N N Y Y and so on statsby "kap A1 B1" k1=r(kappa) se1=R(se), by(hospid)saving(temp1) replace use temp1, clear gen adjustedkappa= I can't seem to figure out how to generate a variable "adjustedkappa" whereby the variable is the sum of the 5 kappas calculated earlier for each individual hospital. I'd like to do the same for the the std error term and the 95% confidence interval. The std error = square root(SUM 1/se(kappahosp(i))^2) Finally, is there a way to program this, so that I could simply write: statsby "kap X Y" k=r(kappa) se=R(se), by(hospid)saving(temp1) replace so I don't have to re-write a statsby line for each item that was observed (A1/B2, A2/B2, A3/B3, ...) Thanks so much! Richard Lenhardt, MD, MPH Assistant Professor of Medicine Division of Pulmonary and Critical Care Medicine Rush University Medical Center Chicago, IL * * 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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