title: A rapidly converging algorithm for exact binomial confidence intervals about the relative risk in follow-up studies with stratified incidence-density data.
abstract: A rapidly converging algorithm is given to calculate exact confidence intervals about the adjusted relative risk in follow-up studies with stratified incidence-density data. The network approach that Mehta developed for tables with person-count numerators and denominators is adapted to tables with person-count numerators and person-time denominators. This algorithm updates an earlier program by Guess et al, yielding the same quantities but with running times that are between ten and a hundred times faster. Applications to Poisson regression are discussed.
authors.affiliation: Merck Sharp & Dohme Research Laboratories, West Point, PA 19486.
authors.forename: H A
authors.initials: HA
authors.lastname: Guess
authors.forename: J E
authors.initials: JE
authors.lastname: Thomas
mesh_terms: D000465:Algorithms; D016010:Binomial Distribution; D016001:Confidence Intervals; D005500:Follow-Up Studies; D006801:Humans; D015994:Incidence; D016012:Poisson Distribution; D012044:Regression Analysis; D012306:Risk