ahr_blinded: Blinded estimation of average hazard ratio

In keaven/gsDesign2: Group Sequential Design with Non-Constant Effect

Blinded estimation of average hazard ratio

Description

Based on blinded data and assumed hazard ratios in different intervals, compute a blinded estimate of average hazard ratio (AHR) and corresponding estimate of statistical information. This function is intended for use in computing futility bounds based on spending assuming the input hazard ratio (hr) values for intervals specified here.

Usage

ahr_blinded(
  Srv = Surv(time = simtrial::Ex1delayedEffect$month, event =
    simtrial::Ex1delayedEffect$evntd),
  intervals = array(3, 3),
  hr = c(1, 0.6),
  ratio = 1
)

Arguments

Srv	input survival object (see Surv); note that only 0=censored, 1=event for Surv
intervals	Vector containing positive values indicating interval lengths where the exponential rates are assumed. Note that a final infinite interval is added if any events occur after the final interval specified.
hr	vector of hazard ratios assumed for each interval
ratio	ratio of experimental to control randomization.

Value

A tibble with one row containing AHR blinded average hazard ratio based on assumed period-specific hazard ratios input in failRates and observed events in the corresponding intervals Events total observed number of events, info statistical information based on Schoenfeld approximation, and info0 (information under related null hypothesis) for each value of totalDuration input; if simple=FALSE, Stratum and t (beginning of each constant HR period) are also returned and HR is returned instead of AHR

Specification

The contents of this section are shown in PDF user manual only.

Examples

## Not run: 
library(simtrial)
library(survival)
ahr_blinded(Srv = Surv(time = simtrial::Ex2delayedEffect$month,
                       event = simtrial::Ex2delayedEffect$evntd),
            intervals = c(4, 100),
            hr = c(1, .55),
            ratio = 1)

## End(Not run)

keaven/gsDesign2 documentation built on Oct. 13, 2022, 8:42 p.m.