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Objective: Identifying the patterning of congenitally absent teeth will contribute to understanding the aetiology of hypodontia. The aim of this study was to investigate patterns of hypodontia in a group of young adults in Sheffield, UK involving specific tooth types, gender differences and maxilla:mandible and left:right correlations., Methods: The patients were 198 unrelated Caucasian young adults (86 males and 112 females) with non-syndromic hypodontia. Statistical methods included the multivariate techniques of cluster analysis and principal components analysis and associated display devices of circular dotplots and biplots. Autologistic regression was used to model the relationship of the presence or absence of a particular tooth to the status of other teeth., Results: The results revealed distinct patterns of dependence. Common patterns included either third molars and second premolars missing in all quadrants and/or combinations of these two tooth types and the incisors. The gender of the patient and the severity of hypodontia did not have a significant effect on patterns of tooth type absence. If a tooth was missing, the odds ratios that the same tooth type in the horizontally or vertically opposite quadrant was also missing were some 20 times higher than if the tooth was present. For diagonally opposite quadrants the dependence was much weaker., Conclusions: These statistical techniques are valuable for increasing understanding of hypodontia and identifying groups of patients for genetic studies.

This article describes an inhomogeneous Poisson point process in the plane with an intensity function based on a Dirichlet tessellation process and a method for using observations on the point process to make fully Bayesian inferences about the underlying tessellation. The method is implemented using a Markov chain Monte Carlo approach. An application to modeling the territories of clans of badgers, Meles meles, is described.