Evaluation of statistical methods for monitoring periodontal disease

Three methods for detecting the progression of periodontal disease based on the change in attachment level on teeth are compared from a statistical point of view. Regardless of gradual or burst disease progression theories, the regression method is found to be the most efficient way to detect changes. The exact false alarm rate is computed when the decision is based on the maximum regression coefficient at all sites during several visits.