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]]