期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2019
卷号：18
期号：2
页码：25-42
DOI：10.22237/jmasm/1604190660
出版社：Wayne State University
摘要：The impact of sparse data conditions was examined among one or more predictor variables in logistic regression and assessed the effectiveness of the Firth (1993) procedure in reducing potential parameter estimation bias. Results indicated sparseness in binary predictors introduces bias that is substantial with small sample sizes, and the Firth procedure can effectively correct this bias.
