frailtyHL (version 2.3)

frailty.vs: Penalized Variable Selection for Frailty Models

Description

frailty.vs is variable-selection procedures (LASSO, SCAD and HL) of fixed effects in frailty models.

Usage

frailty.vs(formula, model, penalty, data, B = NULL, v = NULL, 
alpha = NULL, tun1 = NULL, tun2 = NULL, varfixed = FALSE, varinit = 0.1)

Arguments

formula

A formula object, with the response on the left of a ~ operator, and the terms for the fixed and random effects on the right. e.g. formula=Surv(time,status)~x+(1|id), time : survival time, status : censoring indicator having 1 (0) for uncensored (censored) observation, x : fixed covariate, id : random effect.

model

Log-normal frailty models ("lognorm")

penalty

Penalty functions ("LASSO" or "SCAD" or "HL"))

data

Dataframe used

B

Initial values of fixed effects

v

Initial values of random effects. Zeros are default

alpha

Initial value of variance of random effects.

tun1

Tuning parameter gamma for LASSO, SCAD and HL

tun2

Tuning parameter omega for HL

varfixed

Logical value: if TRUE (FALSE), the value of one or more of the variance terms for the frailties is fixed (estimated).

varinit

Starting values for frailties, the default is 0.1.