gs_info_ahr | R Documentation |
Based on piecewise enrollment rate, failure rate, and dropout rates computes approximate information and effect size using an average hazard ratio model.
gs_info_ahr( enrollRates = tibble::tibble(Stratum = "All", duration = c(2, 2, 10), rate = c(3, 6, 9)), failRates = tibble::tibble(Stratum = "All", duration = c(3, 100), failRate = log(2)/c(9, 18), hr = c(0.9, 0.6), dropoutRate = rep(0.001, 2)), ratio = 1, events = NULL, analysisTimes = NULL )
enrollRates |
enrollment rates |
failRates |
failure and dropout rates |
ratio |
Experimental:Control randomization ratio |
events |
Targeted minimum events at each analysis |
analysisTimes |
Targeted minimum study duration at each analysis |
The AHR()
function computes statistical information at targeted event times.
The tEvents()
function is used to get events and average HR at targeted analysisTimes
.
a tibble
with columns Analysis, Time, AHR, Events, theta, info, info0.
info, info0
contains statistical information under H1, H0, respectively.
For analysis k
, Time[k]
is the maximum of analysisTimes[k]
and the expected time
required to accrue the targeted events[k]
.
AHR
is expected average hazard ratio at each analysis.
The contents of this section are shown in PDF user manual only.
library(gsDesign) library(gsDesign2) # ------------------------ # # Example 1 # # ------------------------ # # Only put in targeted events gs_info_ahr(events = c(30, 40, 50)) # ------------------------ # # Example 2 # # ------------------------ # # Only put in targeted analysis times gs_info_ahr(analysisTimes = c(18, 27, 36)) # ------------------------ # # Example 3 # # ------------------------ # # Some analysis times after time at which targeted events accrue # Check that both Time >= input analysisTime and Events >= input events gs_info_ahr(events = c(30, 40, 50), analysisTimes = c(16, 19, 26)) gs_info_ahr(events = c(30, 40, 50), analysisTimes = c(14, 20, 24))
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