betaEstFam: Estimate the Fixed Effect Parameter for the Frailty Model

In groupedSurv: Efficient Estimation of Grouped Survival Models Using the Exact Likelihood Function

Estimate the Fixed Effect Parameter for the Frailty Model

Description

A method to estimate the fixed effect parameter for a frailty model accounting for family structure of related individuals (e.g., trios). The input data is assumed to be organized such that records for each family occur consecutively, and that records for offspring precede those for parents. The variance matrix for the random effects is assumed to be of the form var*K, where K is a matrix of kinship coefficients between family members. The following family structures are permitted: (Individual), (Offspring, Offspring), (Offspring, Parent), (Offspring, Parent, Parent), and (Offspring, Offspring, Parent, Parent). Other family structures have not been implemented.

Usage

  betaEstFam(x, fam_group, fam_role, alpha, var, gtime, delta, lower, upper)  	

Arguments

x	Vector of numeric variables of interest for each sample.
fam_group	Vector of family IDs for each sample.
fam_role	Vector of indicators for the role within a family of each sample, i.e., {"Offspring","Mother","Father"}, or {"o","m","f"}.
alpha	Vector of baseline survival rates for each time interval.
var	Scalar for frailty variance.
gtime	Vector of observed survival times for each sample.
delta	Vector of event indicators for each sample: 1 indicates observed event, 0 indicates censored.
lower	Scalar for the lower bound of the fixed effect parameter estimation search region.
upper	Scalar for the upper bound of the fixed effect parameter estimation search region.

Value

Scalar estimate of the fixed effect parameter.

Examples

# Generate dummy data	
x     <- c(0, 1, 1, 1, 2, 2, 0, 0, 0)
fam_group <- c('1', '1', '1', '2', '2', '2', '3', '3', '3')
fam_role  <- c("o","f","m","o","f","m","o","f","m")
alpha <- c(0.7500000, 0.6666667, 0.5000000, 0.0000000)
var   <- 0.2
gtime <- c(1, 3, 3, 2, 1, 1, 2, 3, 1)
delta <- c(1, 0, 1, 1, 1, 0, 1, 0, 1)
lower <- 0
upper <- 2

#res   <- betaEstFam(x, fam_group, fam_role, alpha, var, gtime, delta, lower, upper) 
#res

groupedSurv documentation built on Sept. 29, 2023, 1:06 a.m.