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 = survival::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 forSurv- 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
Examples
if (FALSE) {
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)
}