tau.fit: Estimate the Tau Process

In tauProcess: Tau Measure with Right-Censored Data

Estimate the Tau Process

Description

Estimate the tau process at specified time points. The estimated variances at the last time point under complete randomization design and random allocation rule (urn model) are provided.

Usage

tau.fit(data, t = numeric())

Arguments

data	a data.frame consisting of arm, surv.time, event.
t	a sequence of specified times. If the user do not specify the sequence, the default is an equally-spaced sequence from 0 to the last identified time.

Details

The estimation and inference procedure are proposed by Yi-Cheng Tai, Weijing Wang and Martin T. Wells. The value of tau measure serves as a clinically meaningful measure of treatment effect. It supplements the traditional hazard ratio (HR) under nonproportional hazard scenario.

Value

an object of class "tauFit" with components

N0	number of individuals with arm=0
N1	number of individuals with arm=1
t	the specified truncation time
tau	the estimated value of tau measure
var.r	the estimated variance under random grouping design (complete randomization design)
var.f	the estimated variance under fixed grouping design (random allocation rule / urn model)

Examples

tau.fit(data = pbc)

tauProcess documentation built on Sept. 18, 2023, 9:08 a.m.