Log-Logistic Regression Models for Survival Data
描述了一种对数逻辑斯蒂回归模型，其风险函数随时间收敛，适用于癌症生存数据，并在GLIM中拟合，以肺癌数据为例。
The log‐logistic distribution has a non‐monotonic hazard function which makes it suitable for modelling some sets of cancer survival data. A log‐logistic regression model is described in which the hazard functions for separate samples converge with time. This also provides a linear model for the log odds on survival by any chosen time. The model is fitted on GLIM and an example is given of its use with lung cancer survival data.