AFFECT: Accelerated Functional Failure Time Model with...

In AFFECT: Accelerated Functional Failure Time Model with Error-Contaminated Survival Times

Accelerated Functional Failure Time Model with Error-Contaminated Survival Times

Description

The package AFFECT, referred to Accelerated Functional Failure time model with Error-Contaminated survival Times, aims to recover the functional covariates under accelerated functional failure time models, where the data are subject to error-prone response and misclassified censoring status. This package primarily contains three functions. data_gen is applied to generate artificial data based on accelerated functional failure time models, including potential covariates, error-prone response and misclassified censoring status. ME_correction is used to do correction for error-prone response variable and misclassified censoring status, and Boosting is used to recover the functional covariates under accelerated functional failure time models.

Usage

AFFECT()

Details

This package aims to estimate functional covariates under an AFT models with error-prone response and and misclassified censoring status. The strategy is to derive an unbiased estimating function by the Buckley-James estimator with measurement error in response and misclassification in censoring status being corrected. Finally. the functional covariates as well as informative covariates under an AFT models can be derived by the boosting procedure.

Value

No return value, called for side effects.

AFFECT documentation built on July 9, 2023, 6:45 p.m.