Wang Hongyue, Peng Jing, Wang Bokai, Lu Xiang, Zheng Julia Z, Wang Kejia, Tu Xin M, Feng Changyong
Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada.
Shanghai Arch Psychiatry. 2017 Apr 25;29(2):124-128. doi: 10.11919/j.issn.1002-0829.217031.
Logistic regression is a popular statistical method in studying the effects of covariates on binary outcomes. It has been widely used in both clinical trials and observational studies. However, the results from the univariate regression and from the multiple logistic regression tend to be conflicting. A covariate may show very strong effect on the outcome in the multiple regression but not in the univariate regression, and vice versa. These facts have not been well appreciated in biomedical research. Misuse of logistic regression is very prevalent in medical publications. In this paper, we study the inconsistency between the univariate and multiple logistic regressions and give advice in the model section in multiple logistic regression analysis.
逻辑回归是研究协变量对二元结局影响的一种常用统计方法。它已广泛应用于临床试验和观察性研究中。然而，单变量回归和多变量逻辑回归的结果往往相互矛盾。一个协变量在多变量回归中可能对结局有很强的影响，但在单变量回归中却没有，反之亦然。这些事实在生物医学研究中并未得到充分认识。逻辑回归的误用在医学出版物中非常普遍。在本文中，我们研究了单变量和多变量逻辑回归之间的不一致性，并在多变量逻辑回归分析的模型部分给出了建议。
