title: Evaluation of statistical methods for monitoring periodontal disease.
abstract: 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.
authors.affiliation: Department of Statistics, University of Florida, Gainesville 32611.
authors.forename: M C
authors.initials: MC
authors.lastname: Yang
authors.forename: R G
authors.initials: RG
authors.lastname: Marks
authors.forename: W B
authors.initials: WB
authors.lastname: Clark
authors.forename: I
authors.initials: I
authors.lastname: Magnusson
mesh_terms: D004846:Epithelial Attachment / Q000473:pathology; D005189:False Positive Reactions; D006801:Humans; D008991:Monitoring, Physiologic; D010510:Periodontal Diseases / Q000175:diagnosis / Q000503:physiopathology*; D012044:Regression Analysis; D013223:Statistics as Topic / Q000379:methods*