Open AccessA Rapidly Converging Algorithm for Exact Binomial Confidence Intervals About the Relative Risk in Follow-up Studies with Stratified Incidence-Density Data
Author(s) -
Harry A. Guess,
Julie E. Thomas
Publication year - 1990
Publication title -
epidemiology
Language(s) - English
Resource type - Journals
eISSN - 1531-5487
pISSN - 1044-3983
DOI - 10.1097/00001648-199001000-00016
Subject(s) - confidence interval , poisson regression , statistics , count data , mathematics , poisson distribution , negative binomial distribution , binomial (polynomial) , incidence (geometry) , relative risk , algorithm , binomial distribution , binomial proportion confidence interval , cdf based nonparametric confidence interval , medicine , population , geometry , environmental health
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.