betaEst: Estimate the Fixed Effect Parameter for Discrete-Time...

In lclGWAS: Efficient Estimation of Discrete-Time Multivariate Frailty Model Using Exact Likelihood Function for Grouped Survival Data

Description

A method to estimate the fixed effect parameter for a multivariate frailty model accounting for family structure of related individuals (i.e., 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 groupings are permitted: (Individual), (Offspring, Offspring), (Offspring, Parent), (Offspring, Parent, Parent), and (Offspring, Offspring, Parent, Parent). Other family structures have not been implemented.

Usage

  betaEst(fam_group, alpha, dtime, delta, g, var, lower, upper)  	

Arguments

fam_group	Vector of family indicators for each sample.
alpha	Vector of baseline survival rates for each time interval.
dtime	Vector of observed discrete survival times for each sample.
delta	Event indicator vector: 1 indicates observed event, 0 indicates censored.
g	Vector of numeric genotypes for each sample.
var	Scalar for frailty variance.
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

A list with one object:

betaEst

Scalar estimate of the fixed effect parameter.

Examples

# Generate dummy data	
fam_group <- rep(1:3,each=3)
alpha <- c(0.7500000, 0.6666667, 0.5000000, 0.0000000)
dtime <- c(1, 3, 3, 2, 1, 1, 2, 3, 1)
delta <- c(1, 0, 1, 1, 1, 0, 1, 0, 1)
g     <- c(0, 1, 1, 1, 2, 2, 0, 0, 0)
var   <- 0.2
res   <- betaEst(fam_group, alpha, dtime, delta, g, var, lower = 0, upper = 2) 
res

lclGWAS documentation built on May 2, 2019, 2:46 p.m.