hlike.frailty {frailtyHL}

Competing Risk Frialty Models using H-Likelihood

Description

Perform hierarchical likelihood estimation of the univariate frailty model, cause-specific frailty model and subhazard frailty model. Assuming either a univariate normal or multivariate normal distribution for the random effects V, where different covariance structures can be assumed for the multivariate normal distribution.

Usage

hlike.frailty(formula, data, inits, order = 1, frailty.cov = "none", subHazard = FALSE, 
alpha = 0.05, MAX.ITER = 100, TOL = 1e-06)

Arguments

formula

left-hand side is a CmpRsk object (see details), right-hand side is predictors (currently limited to numeric main effects), must include a cluster term that identifies the cluster variable.

data

dataframe containing the variables used in the formula

inits

list of initial values, three named components: beta, v and theta

order

numeric, order of the Laplace approximation, 0=no order, 1=first-order, 2=second-order; second-order only applies to models with a univariate normal distribution

frailty.cov

character string "none", "independent" or "unstructured" specifying the covariance structure for a multivariate normal distribution; "none" indicates univariate normal distribution

subHazard

logical, if TRUE fits the subhazard frailty model

alpha

numeric, 100(1-alpha) percent confidence intervals

MAX.ITER

numeric, maximum number of iterations

TOL

numeric, tolerance limit