mets (version 1.2)

phreg: Fast Cox PH regression

Description

Fast Cox PH regression

Usage

phreg(formula, data, ...)

Arguments

formula

formula with 'Surv' outcome (see coxph)

data

data frame

...

Additional arguments to lower level funtions

Examples

simcox <- function(n=1000, seed=1, beta=c(1,1), entry=TRUE) {
  if (!is.null(seed))
    set.seed(seed)
  library(lava)
  m <- lvm()
  regression(m,T~X1+X2) <- beta
  distribution(m,~T+C) <- coxWeibull.lvm(scale=1/100)
  distribution(m,~entry) <- coxWeibull.lvm(scale=1/10)
  m <- eventTime(m,time~min(T,C=0),"status")
  d <- sim(m,n);
  if (!entry) d$entry <- 0
  else d <- subset(d, time>entry,select=-c(T,C))
  return(d)
}
## Not run: ------------------------------------
# n <- 10;
# d <- mets:::simCox(n); d$id <- seq(nrow(d)); d$group <- factor(rbinom(nrow(d),1,0.5))
# 
# (m1 <- phreg(Surv(entry,time,status)~X1+X2,data=d))
# (m2 <- coxph(Surv(entry,time,status)~X1+X2+cluster(id),data=d))
# (coef(m3 <-cox.aalen(Surv(entry,time,status)~prop(X1)+prop(X2),data=d)))
# 
# 
# (m1b <- phreg(Surv(entry,time,status)~X1+X2+strata(group),data=d))
# (m2b <- coxph(Surv(entry,time,status)~X1+X2+cluster(id)+strata(group),data=d))
# (coef(m3b <-cox.aalen(Surv(entry,time,status)~-1+group+prop(X1)+prop(X2),data=d)))
# 
# m <- phreg(Surv(entry,time,status)~X1*X2+strata(group)+cluster(id),data=d)
# m
# plot(m,ylim=c(0,1))
## ---------------------------------------------