gsDesign2 (version 1.1.2)

gs_info_ahr: Information and effect size based on AHR approximation

Description

Based on piecewise enrollment rate, failure rate, and dropout rates computes approximate information and effect size using an average hazard ratio model.

Usage

gs_info_ahr(
  enroll_rate = define_enroll_rate(duration = c(2, 2, 10), rate = c(3, 6, 9)),
  fail_rate = define_fail_rate(duration = c(3, 100), fail_rate = log(2)/c(9, 18), hr =
    c(0.9, 0.6), dropout_rate = 0.001),
  ratio = 1,
  event = NULL,
  analysis_time = NULL,
  interval = c(0.01, 1000)
)

Value

A data frame with columns Analysis, Time, AHR, Events, theta, info, info0. info, and info0 contain statistical information under H1, H0, respectively. For analysis k, Time[k] is the maximum of analysis_time[k] and the expected time required to accrue the targeted event[k]. AHR is the expected average hazard ratio at each analysis.

Arguments

enroll_rate

Enrollment rates.

fail_rate

Failure and dropout rates.

ratio

Experimental:Control randomization ratio.

event

Targeted minimum events at each analysis.

analysis_time

Targeted minimum study duration at each analysis.

interval

An interval that is presumed to include the time at which expected event count is equal to targeted event.

Specification

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

Details

The ahr() function computes statistical information at targeted event times. The expected_time() function is used to get events and average HR at targeted analysis_time.

Examples

library(gsDesign)
library(gsDesign2)

# Example 1 ----
# \donttest{
# Only put in targeted events
gs_info_ahr(event = c(30, 40, 50))
# }
# Example 2 ----

# Only put in targeted analysis times
gs_info_ahr(analysis_time = c(18, 27, 36))

# Example 3 ----
# \donttest{
# Some analysis times after time at which targeted event accrue
# Check that both Time >= input analysis_time and event >= input event
gs_info_ahr(event = c(30, 40, 50), analysis_time = c(16, 19, 26))
gs_info_ahr(event = c(30, 40, 50), analysis_time = c(14, 20, 24))
# }