phreg: Fast Cox PH regression

In mets: Analysis of Multivariate Event Times

Fast Cox PH regression

Description

Fast Cox PH regression Robust variance is default variance with the summary.

Usage

phreg(formula, data, offset = NULL, weights = NULL, ...)

Arguments

formula	formula with 'Surv' outcome (see coxph)
data	data frame
offset	offsets for cox model
weights	weights for Cox score equations
...	Additional arguments to lower level funtions

Details

influence functions (iid) will follow numerical order of given cluster variable so ordering after $id will give iid in order of data-set.

Author(s)

Klaus K. Holst, Thomas Scheike

Examples

data(TRACE)
dcut(TRACE) <- ~.
out1 <- phreg(Surv(time,status==9)~vf+chf+strata(wmicat.4),data=TRACE)
out2 <- phreg(Event(time,status)~vf+chf+strata(wmicat.4),data=TRACE)
## tracesim <- timereg::sim.cox(out1,1000)
## sout1 <- phreg(Surv(time,status==1)~vf+chf+strata(wmicat.4),data=tracesim)
## robust standard errors default 
summary(out1)
out1 <- phreg(Surv(time,status!=0)~vf+chf+strata(wmicat.4),data=TRACE)
summary(out2)

par(mfrow=c(1,2))
bplot(out1)
## bplot(sout1,se=TRUE)

## computing robust variance for baseline
rob1 <- robust.phreg(out1)
bplot(rob1,se=TRUE,robust=TRUE)

## making iid decomposition of regression parameters
betaiiid <- lava::iid(out1)

## making iid decomposition of baseline at a specific time-point
Aiiid <- mets:::IIDbaseline.phreg(out1,time=30)

mets documentation built on May 29, 2024, 3:51 a.m.