TVQRLB: Quantile Regression Model with Time-Varying Covariates under...

In ZexiCAI/TVQRLB: Quantile Regression Model with Time-Varying Covariates under Length-Biased Sampling

Description

Fits a quantile regression model to the provided dataset where the covariates are viewed as time-dependent and the sampling is length-biased. The parameters are obtained by minimizing the Euclidean norm of certain estimating equations. For the standard error estimation, standard multiplier bootstrap method is used.

Usage

TVQRLB(dataset, betao, bootstrap_time, qtile)

Arguments

dataset	The survival data.
betao	The initial estimate for the parameter.
bootstrap_time	The bootstrapping time for multiplier bootstrap.
qtile	The quantile level used to conduct the quantile regression.

Value

This function returns a list of lists with each list containing four elements:

• qtile, the quantile level specified to fit the model

• beta_est, the estimated value of parameter

• mean_bootstrap, the mean of bootstrap estimates

• sd_bootstrap, the standard error of bootstrap estimates

References

Cai, Z. and Sit, T. (2018+), "Quantile regression model with time-varying covariates under length-biased sampling," Working Paper.

Jin, Z., Lin, D., Wei, L., and Ying, Z. (2003), "Rank-based inference for the accelerated failure time model," Biometrika, 90, 341-353.

Examples

TVQRLB(fixedCP.cen20, c(-1, 0.5, 1.5), 100, 0.5)
TVQRLB(fixedCP.cen40, c(-1, 0.5, 1.5), 100, 0.5)
TVQRLB(fixedCP.cen60, c(-1, 0.5, 1.5), 100, 0.5)
TVQRLB(exponCP.cen20, c(-1, 0.5, 1.5), 100, 0.5)
TVQRLB(exponCP.cen40, c(-1, 0.5, 1.5), 100, 0.5)
TVQRLB(exponCP.cen60, c(-1, 0.5, 1.5), 100, 0.5)

ZexiCAI/TVQRLB documentation built on Dec. 30, 2019, 6:02 p.m.