Computing Distributions for Exact Logistic Regression
针对小样本或稀疏数据结构下渐近近似不准确的问题，研究了精确逻辑回归的分布计算方法，对临床和流行病学研究有用。
Logistic regression is a commonly used technique for the analysis of retrospective and prospective epidemiological and clinical studies with binary response variables. Usually this analysis is performed using large sample approximations. When the sample size is small or the data structure sparse, the accuracy of the asymptotic approximations is in question. On other occasions, singularity of the covariance matrix of parameter estimates precludes asymptotic analysis.