LikI.cmprsk: Second step log-likelihood function under independence...

In depCensoring: Statistical Methods for Survival Data with Dependent Censoring

Second step log-likelihood function under independence assumption.

Description

This function defines the log-likelihood used to estimate the second step in the competing risks extension assuming independence of some of the competing risks in the model described in Willems et al. (2024+).

Usage

LikI.cmprsk(par, data, eoi.indicator.names, admin, conf, cf)

Arguments

par	Vector of all second step model parameters, consisting of the regression parameters, variance-covariance matrix elements and transformation parameters.
data	Data frame resulting from the 'uniformize.data.R' function.
eoi.indicator.names	Vector of names of the censoring indicator columns pertaining to events of interest. Events of interest will be modeled allowing dependence between them, whereas all censoring events (corresponding to indicator columns not listed in eoi.indicator.names) will be treated as independent of every other event.
admin	Boolean value indicating whether the data contains administrative censoring.
conf	Boolean value indicating whether the data contains confounding and hence indicating the presence of Z and W
cf	"Control function" to be used. This can either be the (i) estimated control function, (ii) the true control function, (iii) the instrumental variable, or (iv) nothing (cf = NULL). Option (ii) is used when comparing the two-step estimator to the oracle estimator, and option (iii) is used to compare the two-step estimator with the naive estimator.

Value

Log-likelihood evaluation for the second step in the esimation procedure.

References

Willems et al. (2024+). Flexible control function approach under competing risks (in preparation).

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