r语言医学数据分析实战pdf 下载 r语言与医学统计

Syntax

√输入1：

install.packages("survival")
library(survival)
install.packages("survminer")
library(survminer)
fittime, status) ~ sex, data = lung)
ggsurvplot(fit,   fun = "pct",  title = "                                  Survival Curves",
           font.title    = c(16, "bold", "darkblue"),   
           pval = "P=0.001",  = TRUE,.style = "step", palette = "lancet",
           surv.median.line = "hv",  cumevents = TRUE,  ncensor.plot = TRUE,censor.shape = "+",
           risk.table = TRUE,tables.height = 0.18, 
           risk.table.col = "strata",
           risk.table.y.text.col = TRUE, cumevents.col ="strata",
           font.x = c(14, "bold.italic", "red"),
           font.y = c(14, "bold.italic", "darkred"),
           font.tickslab = c(12, "plain", "darkgreen"),
           legend.title = "Sex",
           legend.labs = c("Male","Female"),legend = "top")

fun=  "event" for cumulative events,"cumhaz" for the cumulative hazard function or "pct" for survival probability in percentage.

√结果1：




√输入2：

splots splots[[1]]                           risk.table = TRUE,
                          tables.y.text = FALSE,
                          ggtheme = theme_light())
splots[[2]]                           risk.table = TRUE,
                          tables.y.text = FALSE,
                          ggtheme = theme_grey()) 
arrange_ggsurvplots(splots, print = TRUE,
                    ncol = 2, nrow = 1, risk.table.height = 0.25)

√结果2：




√输入3：From survminer v0.4.0

lung1 <- lunglung1$sex <-as.factor( ifelse(lung1$sex == 1,"Male", "Female"))fit2 <- coxph(Surv(time, status) ~sex + age,data = lung1)ggcoxadjustedcurves(fit2, data=lung1,variable=lung1$sex,legend.title = "Sex", palette = "jco",individual.curves=TRUE,curve.size=1,      curve.alpha=0.05,ggtheme=theme_gray())

The function ggcoxadjustedcurves() from the survminer package plots  
Adjusted Survival Curves for Cox Proportional Hazards Model. Adjusted
Survival Curves show how a selected factor influences survival estimated
from a Cox model.
Note that these curves differ from Kaplan Meier estimates since they
present expected survival based on given Cox model.

√结果3：