生存分析與cox回歸

# setwd('E:/醫(yī)學(xué)統(tǒng)計(jì)學(xué)（第4版）/各章例題SPSS數(shù)據(jù)文件') data_19_2 <-
# haven::read_sav('例19-02.sav') data_19_1 <- haven::read_sav('例19-01.sav') data_19_3 <-
# haven::read_sav('例19-03.sav') data_19_5 <- haven::read_sav('例19-05.sav') save(data_19_2,
# file='19_2.Rdata') save(data_19_5, file='19_5.Rdata')
load(url("https://github.com/x2yline/Rdata/raw/master/mediacl_statistics/19_2.Rdata"))
load(url("https://github.com/x2yline/Rdata/raw/master/mediacl_statistics/19_5.Rdata"))

par(family = "simhei")
library(survival)

CPCOLS <- c("#FF0A58", "#AB9E9E")
CPCOLS <- c("#F01641", "#A19999")

## 生存分析
fit2 <- survfit(Surv(time, status) ~ group, data = data_19_2)
plot(fit2, lty = c(1, 1), ylab = "生存率", xlab = "生存時(shí)間（月）", bty = "n", main = "生存曲線", 
    col = c(CPCOLS[1], CPCOLS[2]), lwd = 2, mark.time = T, mark = 19, cex = 1.1)

legend(40, 1, c("甲種手術(shù)方式", "乙種手術(shù)方式", "刪失"), lty = c(1, 1, NA), pch = c(NA, NA, 
    16), col = c(CPCOLS[1], CPCOLS[2], CPCOLS[1]), lwd = 2, bty = "n", cex = 0.8)

生存分析曲線

diff_sur <- survdiff(Surv(time, status) ~ group, data = data_19_2)
pchisq(q = diff_sur$chisq, df = 1, lower.tail = FALSE)
## [1] 0.003089351

## http://sites.stat.psu.edu/~drh20/R/html/survival/html/plot.survfit.html


## cox回歸分析
fit5 = coxph(Surv(t, y) ~ X4 + X5, data = data_19_5)
# plot(survfit( fit5))
fit5.sum <- summary(fit5)
fit5.sum[["coefficients"]]
##          coef exp(coef)  se(coef)         z    Pr(>|z|)
## X4 -1.7830043 0.1681323 0.5478848 -3.254342 0.001136555
## X5  0.9395114 2.5587308 0.4446201  2.113066 0.034595151