Yusuf O B, Bamgboye E A, Afolabi R F, Shodimu M A
Afr J Med Med Sci. 2014 Sep;43(3):195-204.
Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it.
This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013.
Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted.
A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles.
Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.
逻辑回归模型在健康研究中被广泛用于描述和预测目的。不幸的是，当最大似然算法不收敛时，大多数研究人员有时并未意识到这些技术的基本原理已经失效。年轻研究人员，尤其是研究生，可能不知道为什么会出现准分离或完全分离问题，如何识别它以及如何解决它。
本研究旨在严格评估2004年至2013年在一份非洲医学与医学科学杂志上发表的采用逻辑回归分析的文章中的收敛问题。
描述了准分离或完全分离问题，并用国家人口与健康调查数据集进行了说明。对采用逻辑回归的文章进行了严格评估。
共审查了581篇文章，其中40篇（6.9%）使用了二元逻辑回归。24篇（60.0%）在方法中说明了使用逻辑回归模型，而没有一篇文章评估模型拟合情况。只有3篇（12.5%）正确描述了程序。在使用逻辑回归模型的40篇文章中，有6篇（15.0%）出现了收敛问题。
在2004年至2013年发表的研究中，逻辑回归的报告往往较差。我们的研究结果表明，研究人员可能并未很好地理解该程序，因为很少有人在报告中描述这个过程，而且可能完全没有意识到收敛问题或如何处理它。
