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Periodontal probing depth is a measure of periodontitis severity. We developa Bayesian hierarchical model linking true pocket depth to both observed andrecorded values of periodontal probing depth, while permitting correlationamong measures obtained from the same mouth and between duplicate examiners'measures obtained at the same periodontal site. Periodontal site-specificexaminer effects are modeled as arising from a Dirichlet process mixture,facilitating identification of classes of sites that are measured with similarbias. Using simulated data, we demonstrate the model's ability to recoverexaminer site-specific bias and variance heterogeneity and to providecluster-adjusted point and interval agreement estimates. We conclude with ananalysis of data from a probing depth calibration training exercise.

A semi-parametric Bayesian model of inter- and intra-examiner agreement for periodontal probing depth