Statistics and Data Analysis

John T. Shelton, Andrew Siegel
1989 Technometrics  
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. Hirji, Mehta, and Patel (1987) developed an efficient
more » ... oped an efficient algorithm for generating the required conditional distributions, thus making these methods computationally available. This paper discusses the theory and methods for exact logistic regression and illustrates their application in Version 8 of the SAS R System with new facilities in the LOGISTIC procedure. ½ ½ , let ½ if the subject died, ¼ otherwise, and È Ö ½ Ü µ. Then the linear logistic model for this problem is ÐÓ Ø´ µ ÐÓ ½ « · Ü ¬, which fits a common intercept and slope for the subjects. In the PROC LOGISTIC invocation below, the EXACT statement requests an exact analysis and the ESTIMATE option produces exact parameter estimates. proc logistic data=dose descending; model Deaths/Total = Dose; exact Dose / estimate=both; run; Statistics and Data Analysis
doi:10.2307/3556154 fatcat:qppmkikj5rec3gvm55ij4lznde