A semi-parametric estimation method for the Cox model with left-truncated data using augmented information from the marginal of truncation times.
This is an R package to implement the semi-parametric estimation method for the Cox model introduced in the paper A Pairwise Likelihood Augmented Estimator for the Cox Model under Left-Truncation by Wu et al. (2015). It gives more efficient estimates for left-truncated survival data under the Cox model by making use of the marginal survival information upto the entry of the subjects. The method will be most helpful when the sample size or number of observed events are not large and estimation efficiency is more of a concern.
This package can be installed from github with the help of
The main wrapper function
PLAC() calls the appropriate working function according to the covariate types in the dataset. For example,
library(plac)# When only time-invariant covariates are involveddat1 = sim.ltrc(n = 50)$datPLAC(ltrc.formula = Surv(As, Ys, Ds) ~ Z1 + Z2,ltrc.data = dat1, td.type = "none")# When there is a time-dependent covariate that is independent of the truncation timedat2 = sim.ltrc(n = 50, time.dep = TRUE,distr.A = "binomial", p.A = 0.8, Cmax = 5)$datPLAC(ltrc.formula = Surv(As, Ys, Ds) ~ Z,ltrc.data = dat2, td.type = "independent",td.var = "Zv", t.jump = "zeta")# When there is a time-dependent covariate that depends on the truncation timedat3 = sim.ltrc(n = 50, time.dep = TRUE, Zv.depA = TRUE, Cmax = 5)$datPLAC(ltrc.formula = Surv(As, Ys, Ds) ~ Z,ltrc.data = dat3, td.type = "post-trunc",td.var = "Zv", t.jump = "zeta")
For more details on the arguments of the function, please run