Here is a partial answer (I think (?)) A common way to display results of this type is as a "receiver operating characteristic." See: http://en.wikipedia.org/wiki/Receiver_operating_characteristic
It's displayed as a parametric curve where the parameter is the threshold value, the x-value (abscissa) is the false-positive rate and the y value is the true-positive rate. Then, a commonly computed single-number characterization is to compute the area under this curve (AUC) for false-positive rate running from 0 to 1. There are variations on this but I've just described the standard one. There are multiple R-packages that will do all of this for you. One of them is the pROC package. See http://cran.at.r-project.org/web/packages/pROC/pROC.pdf. =============================================================== Date: Sun, 20 Jul 2014 18:28:12 +0100 From: Anoop Shah <anoopss...@gmail.com> To: r-help@r-project.org Subject: [R] dx accuracy measures from raw data Message-ID: <0e7574af-9890-419e-ae9d-978860054...@gmail.com> Content-Type: text/plain Hello R users! I am a medic and have been working with R for about 6 months now. I was hoping to pick someone’s brain about a diagnostic accuracy study that has now been completed. I am trying to derive the sensitivity, specificity, NPV and PPV with the corresponding 95% CI from the raw data. My data is in a data frame as below g.s t1 t2 t3 t3 t4 t5 index Yes 1 1 1 1 1 1 1 Yes 1 1 1 1 1 1 2 Yes 1 1 1 1 1 1 3 Yes 1 1 1 1 1 1 4 Yes 1 1 1 1 1 1 5 Each row represents a patient with a unique id (variable: index). g.s is a binary variable ans represents the results from the gold standard (yes / no). t1 to t5 are the tests at different thresholds being tested. t1 to t5 are all binary variables with 1 as yes and 0 as no. Now i could create separate 2 x 2 tables for each threshold (t1 to t5) against the gold standard and subsequently derive sense, spec, NPV and PPV plus their 95 % CI for each threshold (t1 to t5). I was however wondering if there was a more efficient way to get these results from the raw data in R. Hope I have explained my self clearly and thanks a lot in advance!! Cheers Anoop [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
