| cox.kmi {kmi} | R Documentation |
This function fits Cox proportional hazards models to each imputed data set to estimate the regression coefficients in a proportional subdistribution hazards model, and pools the results.
cox.kmi(formula, imp.data, df.complete = Inf, ...)
formula |
A formula object, with the response on the left of a
~ operator, and the terms on the right. The response must be
a survival object as returned by the Surv
function. |
imp.data |
An object of class kmi. |
df.complete |
Complete data degrees of freedom. |
... |
Further arguments for the coxph
function. |
Fits a Cox proportional hazards model on each imputed data set to
estimate the regression coefficients in a proportional
subdistribution hazards model, and pools the results, using the
MIcombine function of the mitools package.
An object of class cox.kmi including the following components:
coefficients |
Pooled regression coefficient estimates |
variance |
Pooled variance estimate |
nimp |
Number of multiple imputations |
df |
degrees of freedom |
call |
The matched call |
individual.fit |
A list of coxph objects. One for each
imputed data set. |
Arthur Allignol, arthur.allignol@fdm.uni-freiburg.de
coxph,
MIcombine, print.cox.kmi,
summary.cox.kmi
data(icu.pneu)
set.seed(1313)
imp.dat <- kmi(Surv(entry, exit, status) ~ 1, data = icu.pneu,
etype = event, id = id, failcode = 3, nimp = 5)
fit.kmi <- cox.kmi(Surv(entry, exit, event == 3) ~ pneu, imp.dat)
summary(fit.kmi)
### Now using the censoring-complete data
fit <- coxph(Surv(entry, adm.cens.exit, event == 3) ~ pneu, icu.pneu)
summary(fit)