Abbott R D
Am J Epidemiol. 1985 Mar;121(3):465-71. doi: 10.1093/oxfordjournals.aje.a114019.
Logistic regression has been applied to numerous investigations that examine the relationship between risk factors and various disease events. Recently, the ability to consider the time element of event occurrences by proportional hazards models has meant that logistic regression has played a less important role in the analysis of survival data. This paper, however, shows that when event times are grouped into intervals, logistic regression can be adapted to the analysis of such data by modeling the interval when an event occurs. Furthermore, it is shown that results from such an adaptation will often lead to parameter estimates close to those obtained by the proportional hazards model in the grouped event time setting. An illustration of the application of logistic regression to survival analysis is based on data from the Framingham Heart Study.
逻辑回归已应用于众多研究中，这些研究考察了风险因素与各种疾病事件之间的关系。最近，通过比例风险模型考虑事件发生时间因素的能力意味着逻辑回归在生存数据分析中所起的作用已不那么重要。然而，本文表明，当事件时间被分组为区间时，通过对事件发生的区间进行建模，逻辑回归可适用于此类数据的分析。此外，研究表明，这种改编后的结果通常会导致参数估计值接近在分组事件时间设置下通过比例风险模型获得的估计值。基于弗雷明汉心脏研究的数据给出了逻辑回归在生存分析中的应用示例。
