title: A SEMI-PARAMETRIC BAYESIAN MODEL OF INTER- AND INTRA-EXAMINER AGREEMENT FOR PERIODONTAL PROBING DEPTH.
abstract: 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.
authors.affiliation: Department of Public Health Sciences Medical University Of South Carolina Hollings Cancer Center 86 Jonathan Lucas Street Suite 118 MSC 955 Charleston, South Carolina 29425-9550 USA hille@musc.edu.
authors.forename: E G
authors.initials: EG
authors.lastname: Hill
authors.affiliation: Department of Statistics Florida State University 117 North Woodward Avenue P.O. Box 3064330 Tallahassee, Florida 32306-4330 USA slate@stat.fsu.edu.
authors.forename: E H
authors.initials: EH
authors.lastname: Slate
keywords: Agreement; Dirichlet process mixture model; cluster-correlated data; clustering; measurement error; periodontal disease; weighted kappa