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A rapidly converging algorithm for exact binomial confidence intervals about the relative risk in follow-up studies with stratified incidence-density data.

H A Guess·J E Thomas
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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.

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AlgorithmsBinomial DistributionConfidence IntervalsFollow-Up StudiesHumansIncidencePoisson DistributionRegression AnalysisRiskJournal Article

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BibTeXRIS

H A Guess, J E Thomas. 1990. A rapidly converging algorithm for exact binomial confidence intervals about the relative risk in follow-up studies with stratified incidence-density data.. https://doi.org/10.1097/00001648-199001000-00016

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