Plots the predicted survival function from a coxph
object, setting covariates to particular values.
1 2 3 
x 
a 
newdata 
a data frame containing (combinations of) values to which predictors are set; optional. 
typical 
function to use to compute "typical" values of numeric predictors. 
byfactors 
if 
col 
colors for lines. 
lty 
linetypes for lines; if missing, defaults to 1 to number required. 
conf.level 
level for confidence intervals; note: whether or not confidence intervals are
plotted is determined by 
... 
arguments passed to 
If newdata
is missing then all combinations of levels of factorpredictors (or strata),
if present, are combined with "typical" values of numeric predictors.
Invisibly returns the summary
resulting from applying survfit.coxph
to the coxph
object.
John Fox jfox@mcmaster.ca.
John Fox, Marilia Sa Carvalho (2012). The RcmdrPlugin.survival Package: Extending the R Commander Interface to Survival Analysis. Journal of Statistical Software, 49(7), 132.
coxph
, survfit.coxph
,
plot.survfit
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  require(survival)
cancer$sex < factor(ifelse(cancer$sex == 1, "male", "female"))
mod.1 < coxph(Surv(time, status) ~ age + wt.loss, data=cancer)
plot(mod.1)
plot(mod.1, typical=function(x) quantile(x, c(.25, .75)))
mod.2 < coxph(Surv(time, status) ~ age + wt.loss + sex, data=cancer)
plot(mod.2)
mod.3 < coxph(Surv(time, status) ~ (age + wt.loss)*sex, data=cancer)
plot(mod.3)
mod.4 < coxph(Surv(time, status) ~ age + wt.loss + strata(sex), data=cancer)
plot(mod.4)
mods.1 < survreg(Surv(time, status) ~ age + wt.loss, data=cancer)

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