make.timedep.dataset: Create Dataset for Time-dependent Covariate Proportional...

In kyotil: Utility Functions for Statistical Analysis Report Generation and Monte Carlo Studies

Create Dataset for Time-dependent Covariate Proportional Hazard Model Analaysi

Description

Returns a data frame that is suitable for time-dependent covariate Cox model fit.

Usage

make.timedep.dataset(dat, X, d, baseline.ageyrs, t.1, t.2 = NULL)

Arguments

dat	data frame
X	string. Name of the followup time column in dat. Unit needs to be years.
d	string. Name of the followup time column in dat.
baseline.ageyrs	string. Name of the followup time column in dat.
t.1	numerical. Cutoff for age group
t.2	numerical. Second cutoff for age group

Details

The function assumes that the followup length is such that only one change of age group is possible.

Value

Returns a data frame with the following columns added: tstart, tstop, .timedep.agegrp, .baseline.agegrp

tstart	left bound of time interval
tstop	right bound of time interval
.timedep.agegrp	time-dependent age group
.baseline.agegrp	baseline age group

Author(s)

Youyi Fong

References

Therneau, T. and Crowson, C. Using Time Dependent Covariates and Time Dependent Coefficients in the Cox Model. A vignette from the R package surival.

Examples

library(survival)

n=3000; followup.length=5; incidence.density=0.015; age.sim="continuous"

dat.0=sim.dat.tvarying.two(n, followup.length, incidence.density, age.sim, seed=1)
dat=subset(dat.0, for.non.tvarying.ana, select=c(ptid, X, d, baseline.age, trt))
dat.timedep = make.timedep.dataset (dat, "X", "d", "baseline.age", 6)
coxph(Surv(tstart,tstop,d) ~ trt*.timedep.agegrp, dat.timedep)

kyotil documentation built on Nov. 28, 2023, 1:09 a.m.