SolveL: Cumulative hazard function of survival time under dependent...

In depCensoring: Statistical Methods for Survival Data with Dependent Censoring

Cumulative hazard function of survival time under dependent censoring

Description

This function estimates the cumulative hazard function of survival time (T) under dependent censoring (C). The estimation makes use of the estimating equations derived based on martingale ideas.

Usage

SolveL(
  theta,
  resData,
  X,
  W,
  cop = c("Frank", "Gumbel", "Normal"),
  dist = c("Weibull", "lognormal")
)

Arguments

theta	Estimated parameter values/initial values for finite dimensional parameters
resData	Data matrix with three columns; Z = the observed survival time, d1 = the censoring indicator of T and d2 = the censoring indicator of C.
X	Data matrix with covariates related to T
W	Data matrix with covariates related to C. First column of W should be ones
cop	Which copula should be computed to account for dependency between T and C. This argument can take one of the values from c("Gumbel", "Frank", "Normal"). The default copula model is "Frank".
dist	The distribution to be used for the dependent censoring C. Only two distributions are allowed, i.e, Weibull and lognormal distributions. With the value "Weibull" as the default.

Value

This function returns an estimated hazard function, cumulative hazard function and distinct observed survival times;

Examples

n = 200
beta = c(0.5)
lambd = 0.35
eta = c(0.9,0.4)
X = cbind(rbinom(n,1,0.5))
W = cbind(rep(1,n),rbinom(n,1,0.5))
frank.cop <- copula::frankCopula(param = 5,dim = 2)
U = copula::rCopula(n,frank.cop)
T1 = (-log(1-U[,1]))/(lambd*exp(X*beta))         # Survival time'
T2 = (-log(1-U[,2]))^(1.1)*exp(W%*%eta)          # Censoring time
A = runif(n,0,15)                                # administrative censoring time
Z = pmin(T1,T2,A)
d1 = as.numeric(Z==T1)
d2 = as.numeric(Z==T2)
resData = data.frame("Z" = Z,"d1" = d1, "d2" = d2)
theta = c(0.3,1,0.3,1,2)

# Estimate cumulative hazard function
cumFit <- SolveL(theta, resData,X,W)
cumhaz = cumFit$cumhaz
time = cumFit$times

# plot hazard vs time

plot(time, cumhaz, type = "l",xlab = "Time",
ylab = "Estimated cumulative hazard function")

depCensoring documentation built on April 4, 2025, 1:52 a.m.