coxHazardPureRisk {WeightCalibSurvival} | R Documentation |
Estimate pure risk from Cox proportional hazards model given a set of covariates.
coxHazardPureRisk(coxHazObj, newdata, risk.time, risk.time0=0, new.risk.col="pureRisk")
coxHazObj |
A fitted model from addHazard. |
newdata |
Data frame for covariate-specific pure risk estimation. |
risk.time |
Projection time for pure risk. |
risk.time0 |
Initial projection time for pure risk. The default is 0. |
new.risk.col |
New column name added to |
The covariates used in coxHazObj
must also be in newdata
, and
they must be of the same type.
The data frame newdata
with one additional column containing
the estimated pure risk.
Yei Eun Shin syeeun@gmail.com
Shin YE, Pfeiffer RM Graubard BI, Gail MH. Weight calibration to improve efficiency for estimating pure risks from the additive hazards model with the nested case-control design. Biometrics. 2020;1-13. https://doi.org/10.1111/biom.13413
data(sample_data, package="WeightCalibSurvival") # Set the input arguments ncc.subset <- sample_data[, "ind.ph2"] outcome.var <- "ind.fail" time.vars <- "eventime" covars <- c("X1", "X2", "Z1", "Z2") anc.covars <- "U" risk.time <- 8 inclProb.var <- "incl.prob" fit <- coxHazard(sample_data, ncc.subset, outcome.var, time.vars, covars, anc.covars, risk.time, inclProb.var=inclProb.var) newdata <- sample_data[ncc.subset, ] ret <- coxHazardPureRisk(fit$with.calibration, newdata, risk.time) ret[1:5, ]