Data Analysis Papers
Performing Exact Logistic Regression with the SAS System—Revised 2009
Robert Derr, SAS Institute Inc., Revised 2009.
Abstract
Exact logistic regression has become an important analytical technique, especially in the pharmaceutical industry, since the usual asymptotic methods for analyzing small, skewed, or sparse data sets are unreliable. Inference based on enumerating the exact distributions of sufficient statistics for parameters of interest in a logistic regression model, conditional on the remaining parameters, is computationally infeasible for many problems. Efficient algorithms for generating the required conditional distributions were introduced in Hirji, Mehta, and Patel (1987) and Mehta, Patel, and Senchaudhuri (1992, 2000), thus making these methods computationally available. This paper discusses the theory and methods for exact logistic regression and illustrates their application with the LOGISTIC procedure in SAS/STAT® 9.2 software.
