  Periodontal probing depth is a measure of periodontitis severity. We develop
a Bayesian hierarchical model linking true pocket depth to both observed and
recorded values of periodontal probing depth, while permitting correlation
among measures obtained from the same mouth and between duplicate examiners'
measures obtained at the same periodontal site. Periodontal site-specific
examiner effects are modeled as arising from a Dirichlet process mixture,
facilitating identification of classes of sites that are measured with similar
bias. Using simulated data, we demonstrate the model's ability to recover
examiner site-specific bias and variance heterogeneity and to provide
cluster-adjusted point and interval agreement estimates. We conclude with an
analysis of data from a probing depth calibration training exercise.
