Thursday, November 21, 2019,
Davis Science Building / 301

The first step in identifying biopsy-based markers of kidney disease progression is to assess agreement among pathologists' marker ratings. Unfortunately, existing agreement statistics make assumptions about chance agreement that are often implausible in kidney pathology. We propose a novel agreement statistic that accounts for the empirical probability of chance agreement, estimated by collecting additional data on rater uncertainty for each rating. We also derive a standard error estimator for our proposed agreement statistic. Simulations studies show our proposed statistic has less bias than existing statistics for estimating the probability of agreement after removing chance agreement. Finally, we apply our proposed statistic to a real data example to estimate pathologist agreement in rating kidney biopsy markers.
Davis 301, 4:00 PM
Refreshments at 3:30 PM on the 2nd floor

Open to the Colby community only