estimate_censoring_SL: wrapper for censoring regression SuperLearner
In wilsoncai1992/onestep.survival: One-step TMLE for survival analysis
Description
Usage
Arguments
Value
Examples
View source: R/initial_SL_fit.R
Description
wrapper for censoring regression SuperLearner
Usage
1
2
estimate_censoring_SL(dat, T.uniq, Delta.SL.Lib = c("SL.mean", "SL.glm",
"SL.gam", "SL.earth"))
Arguments
dat
data.frame, with col: T, A, W, Delta
T.uniq
the unique time points of failure
Delta.SL.Lib
library for SuperLearner
Value
h.hat.t matrix, nrow = n.sample, ncol = length(T.uniq);
each row is the predicted conditional hazard h(T=t | T>=t, A, W) for that subject
Examples
1
# TO DO
wilsoncai1992/onestep.survival documentation built on May 29, 2019, 11:58 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Examples
View source: R/initial_SL_fit.R
Description
wrapper for censoring regression SuperLearner
Usage
1 2 | estimate_censoring_SL(dat, T.uniq, Delta.SL.Lib = c("SL.mean", "SL.glm",
"SL.gam", "SL.earth"))
|
Arguments
dat |
data.frame, with col: T, A, W, Delta |
T.uniq |
the unique time points of failure |
Delta.SL.Lib |
library for SuperLearner |
Value
h.hat.t matrix, nrow = n.sample, ncol = length(T.uniq); each row is the predicted conditional hazard h(T=t | T>=t, A, W) for that subject
Examples
1 | # TO DO
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.