Fits a semi-parametric Cox proportional-hazards regression of time-to-event data.
Arguments
- formula
Model formula specifying the regression model, e.g.
Surv(time, event) ~ exposure.- data
Data frame containing the variables of interest.
- ...
Other arguments passed to
survival::coxph().
Value
A coxph object with with additional ertte_coxph and ertte_model
classes used to supply additional methods.
Details
The ertte_coxph() function is a thin wrapper around survival::coxph(),
used to build semi-parametric proportional hazard models for time-to-event
data. One slight difference is that the call to coxph() always sets
model = TRUE, because downstream methods supplied by the ertte package
require the model frame to be accessible from within the return object.
Along similar lines, ertte_coxph() caches the input data frame within
the returned model object, ensuring that it remains accessible to downstream
tools that have access to the model object but not necessarily the original
data frame.
Because the return value is a coxph object, all the usual
methods for survival regression models work unchanged, without needing an
ertte-specific equivalent. This includes summary(), coef(), vcov(),
confint(), predict(), AIC(), BIC(), logLik(), and anova().
Additional methods supplied via the ertte-specific classes include
ertte_predict(), ertte_fun(), and simulate().
Examples
mod <- ertte_coxph(Surv(time, event) ~ aucss, ertte_data)
mod
#> Call:
#> survival::coxph(formula = formula, data = data, model = TRUE)
#>
#> coef exp(coef) se(coef) z p
#> aucss 8.859e-04 1.001e+00 7.515e-05 11.79 <2e-16
#>
#> Likelihood ratio test=110.2 on 1 df, p=< 2.2e-16
#> n= 300, number of events= 232