LikGenNPH: LikGenNPH

In AB5103/doubleCoxr: Parametric Gamma-Frailty Models with Non-Proportional Hazard Functions

Description

This function calculates the neg-loglikelihood for the parametric gamma-frailty model with non-proportional hazard functions

Usage

LikGenNPH(y, D, nf, nk, ncl, dist)

Arguments

y	Vector of parameters in the form y = (ln(a), ln(b), β _{shape}, β _{scale}, ln(σ ^2)) for Weibull hazard function and y = (ln(10^3a), ln(10^2b), β _{shape}, β _{scale}, ln(σ ^2)) for Gompertz hazard function, where a and b are slope and shape parameters, β _{shape} and β _{scale} are the Cox-regression parameters for shape and scale, respectively, and σ ^2 is the variance of frailty. This vector must include at least two parameters, ln(a) and ln(b).
D	A data.frame in which to interpret the variables named in the formula. The data set includes the following fields: time-to-failure and censoring in the case without left truncation or time-of-start, time-of-failure, and censoring in the case with left truncation at the time of begin (censoring must be either 0 for no event or 1 for event); Covariates (continuous or categorical) used in a study (can be empty set).
nf	The number of continuous and binary factors in the data set D corresponding to the covariates used in the Cox-regression for proportional hazard term.
nk	The number of continuous and binary factors in the data set D corresponding to the covariates used in the Cox-regression for shape b.
ncl	The number of clusters in the data set D corresponding to the cluster covariate. Is equal to 0 for the fixed-effect model.
dist	Baseline hazard function ('Weibull' or 'Gompertz').

Value

Neg-loglikelihood

Examples

## Not run: 
LikGenNPH(y, D, nf, nk, ncl, dist)

## End(Not run)

AB5103/doubleCoxr documentation built on Feb. 20, 2022, 2:20 p.m.