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Saddlepoint approximations for small sample logistic regression problems
Author(s) -
Platt Robert W.
Publication year - 2000
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(20000215)19:3<323::aid-sim372>3.0.co;2-d
Subject(s) - inference , mathematics , logistic regression , sequence (biology) , binomial distribution , statistics , binomial regression , econometrics , computer science , artificial intelligence , biology , genetics
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 2×2 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. Copyright © 2000 John Wiley & Sons, Ltd.