Statistical models for data from periodontal research

Abstract

Many factors have been hypothesised either to characterise groups and individuals at risk for periodontal disease or to be markers of periodontal breakdown. In order to identify these as associated either with disease status or progression, a statistical association between the factor and a measure of disease will have to be demonstrated. The statistical modelling of data arising from periodontal research presents special problems. These include the large number of measurements made in each subject, the large magnitude of measurement error compared to the changes in attachment level, the analysis of longitudinal studies, the lack of a measure of instantaneous rate of attachment loss and controversies over the nature of the progression of the disease. We consider statistical methods currently available in the light of these difficulties and identify areas in which further research is necessary.