相关软件（R代码）

# Cox比例风险模型
# install.packages("survival")
library(survival)
data(lung)
# 建立Cox模型
model_cox <- coxph(Surv(time, status) ~ age + sex + ph.ecog, data = lung)
summary(model_cox)
# 检验比例风险假设
# install.packages("survminer")
library(survminer)
cox.zph(model_cox)
# 绘制生存曲线
fit <- survfit(Surv(time, status) ~ sex, data = lung)
ggsurvplot(fit, pval = TRUE, conf.int = TRUE, 
           title = "不同性别患者的生存曲线",
           xlab = "天数", ylab = "生存概率")
# 预测
new_patients <- data.frame(age = c(60, 70), sex = c(1, 2), ph.ecog = c(1, 2))
fit_new <- survfit(model_cox, newdata = new_patients)
plot(fit_new, col = 1:2, xlab = "天数", ylab = "生存概率")
legend("bottomleft", legend = c("患者1", "患者2"), col = 1:2, lty = 1)

2.3.6 线性混合效应模型