extrafrail (version 1.13)

baseCH: Computes the baseline cumulative hazard function.

Description

Provides the baseline cumulative hazard function (\(\Lambda_0\)) for an object with extrafrail class.

Usage

baseCH(t, fit)

Value

a vector with the same length that t, including the baseline cumulative hazard function related to t.

Arguments

t

the vector of times for which the baseline cumulative hazard function should be computed.

fit

an object with extrafrail class.

Author

Diego Gallardo and Marcelo Bourguignon.

Details

Provides the baseline cumulative hazard function. When the baseline distribution is assumed as the Weibull model, this function is \(\Lambda_0(t)=\lambda t^{\rho}\). For the piecewise exponential model, this function is \(\Lambda_0(t)=\sum_{j=1}^L \lambda_j \nabla_j(t)\), where \(\nabla_j(t)=0, \) if \(t<a_{j-1}\), \(\nabla_j(t)=t-a_{j-1}, \) if \(a_{j-1}\leq t < a_{j}\) and \(\nabla_j(t)=a_j-a_{j-1}, \) if \(t\geq a_{j}\), with \(a=(a_0=0, a_1, \ldots, a_{j-1}),\) the corresponding partition time.

References

Gallardo, D.I., Bourguignon, M. (2022) The multivariate weighted Lindley frailty model for cluster failure time data. Submitted.

Examples

# \donttest{
#require(frailtypack)
require(survival)
data(rats, package="frailtyHL")
#Example for WL frailty model
fit.WL <- frailty.fit(survival::Surv(time, status) ~ rx + survival::cluster(litter), 
dist.frail="WL", data = rats)
baseCH(c(80,90,100),fit.WL)
# }