knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(ISwR) # Get melanoma dataset library(survival) library(ROCR) library(evacure) # devtools::load_all()
# Transfer covariates data(melanom) melanom$year <- melanom$days / 365.25 melanom$l.thick <- log(melanom$thick) melanom$sex1 <- melanom$sex == 2 #( 1 = male) melanom$ulc1 <- melanom$ulc == 1 #( 1 = present) median(melanom$year) # median survival time 1 - sum(melanom$status == 1) / nrow(melanom) # Censoring proportion
# Ulceration a <- survfit(Surv(melanom$days/365.25, melanom$status == 1) ~ ulc, data = melanom) plot(a, ylab = "Survival Probability", xlab = "Year", lty = c(2,1), mark.time = T) legend("bottomleft", lty = c(1,2), legend = c("No","Yes"))
# Tumor thickness b <- survfit(Surv(melanom$days/365.25, melanom$status == 1) ~ I(l.thick > median(l.thick) ) , data = melanom) plot(b, ylab = "Survival Probability", xlab = "Year", lty = c(2,1), mark.time = T) legend("bottomleft", lty = c(1,2), legend = c("Above Median","Below Median"))
fit <- smcure1( Surv(melanom$days, melanom$status == 1) ~ sex1 + l.thick + ulc1, cureform = ~ sex1 + l.thick + ulc1, data = melanom, model = "ph", Var = T, em = "smcure" ) printsmcure1(fit, Var = T)
fit1 <- coxph(Surv(melanom$days, melanom$status == 1) ~ sex1 + l.thick + ulc1, data = melanom, x = TRUE) risk <- predict(fit1, type = "risk") # risk from Cox PH model pi <- rep(1, nrow(melanom) ) # set cure probablity always be 1 k.ind(risk = risk, pi = rep(1, nrow(melanom) ), model = "PH") # K-index
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