thetaEst: Estimate the Baseline Survival Rates and Covariate Parameters...

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

Estimate the Baseline Survival Rates and Covariate Parameters for the Grouped Survival Model

Description

A method to estimate the baseline survival rate for each time interval and the covariate nuisance parameters for a grouped survival model. The estimation is conducted under the null hypothesis, i.e., that there is no effect from the variable of interest.

Usage

  thetaEst(Z=NULL, gtime, delta, method="BFGS")  	

Arguments

Z	Optional data.frame or matrix of numeric covariate values for each sample.
gtime	Vector of observed survival times for each sample.
delta	Vector of event indicators for each sample: 1 indicates observed event, 0 indicates censored.
method	String indicating optimization method, passed to stats::optim. Supports "BFGS" and "CG". Default is "BFGS".

Value

A list containing two vectors: alpha, the baseline survival rate for each time interval, and theta, the estimated nuisance parameters of the covariates.

Examples

# Generate dummy data	
cov1  <- c(1, 2, 2, 2, 1, 1, 0, 1, 1)
cov2  <- c(2, 2, 1, 0, 1, 0, 1, 1, 0.5) 
Z     <- cbind(cov1, cov2)
gtime <- c(1, 3, 3, 2, 1, 1, 2, 3, 1)
delta <- c(1, 0, 1, 1, 1, 0, 1, 0, 1)

#res   <- thetaEst(Z, gtime, delta) 
#res

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