riskreg_cens {targeted} | R Documentation |
Binary regression models with right censored outcomes
Description
Binary regression models with right censored outcomes
Usage
riskreg_cens(
response,
censoring,
treatment = NULL,
prediction = NULL,
data,
newdata,
tau,
type = "risk",
M = 1,
call.response = "phreg",
args.response = list(),
call.censoring = "phreg",
args.censoring = list(),
preprocess = NULL,
efficient = TRUE,
control = list(),
...
)
Arguments
response |
Response formula (e.g., Surv(time, event) ~ D + W). |
censoring |
Censoring formula (e.g., Surv(time, event == 0) ~ D + A + W)). |
treatment |
Optional treatment model (ml_model) |
prediction |
Optional prediction model (ml_model) |
data |
data.frame. |
newdata |
Optional data.frame. In this case the uncentered influence function evalued in 'newdata' is returned with nuisance parameters obtained from 'data'. |
tau |
Time-point of interest, see Details. |
type |
"risk", "treatment", "rmst", "brier" |
M |
Number of folds in cross-fitting (M=1 is no cross-fitting). |
call.response |
Model call for the response model (e.g. "mets::phreg"). |
args.response |
Additional arguments to the response model. |
call.censoring |
Similar to call.response. |
args.censoring |
Similar to args.response. |
preprocess |
(optional) Data pre-processing function. |
efficient |
If FALSE an IPCW estimator is returned |
control |
See details |
... |
Additional arguments to lower level data pre-processing functions. |
Details
The one-step estimator depends on the calculation of an integral
wrt. the martingale process corresponding to the counting process N(t) =
I(C>min(T,tau)). This can be decomposed into an integral wrt the counting
process, and the compensator
where the
latter term can be computational intensive to calculate. Rather than
calculating this integral in all observed time points, we can make a
coarser evaluation which can be controlled by setting
control=(sample=N)
.
With N=0
the (computational intensive) standard evaluation is used.##'
Value
estimate object
Author(s)
Klaus K. Holst, Andreas Nordland