title: Saddlepoint approximations for small sample logistic regression problems.
abstract: Double saddlepoint approximations provide quick and accurate approximations to exact conditional tail probabilities in a variety of situations. This paper describes the use of these approximations in two logistic regression problems. An investigation of regression analysis of the log-odds ratio in a sequence or set of 2x2 tables via simulation studies shows that in practical settings the saddlepoint methods closely approximate exact conditional inference. The double saddlepoint approximation in the test for trend in a sequence of binomial random variates is also shown, via simulation studies, to be an effective approximation to exact conditional inference.
authors.affiliation: Departments of Epidemiology and Biostatistics and Pediatrics, McGill University, Montreal, Canada. robertp@epid.lan.mcgill.ca
authors.forename: R W
authors.initials: RW
authors.lastname: Platt
mesh_terms: D016015:Logistic Models; D015233:Models, Statistical; D016017:Odds Ratio; D011336:Probability