gsDesign2 (version 1.1.3)

pw_info: Average hazard ratio under non-proportional hazards

Description

Provides a geometric average hazard ratio under various non-proportional hazards assumptions for either single or multiple strata studies. The piecewise exponential distribution allows a simple method to specify a distribution and enrollment pattern where the enrollment, failure and dropout rates changes over time.

Usage

pw_info(
  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),
  total_duration = 30,
  ratio = 1
)

Value

A data frame with time (from total_duration), stratum, t, hr (hazard ratio), event (expected number of events), info

(information under given scenarios), info0 (information under related null hypothesis), and n (sample size) for each value of total_duration

input

Arguments

enroll_rate

An enroll_rate data frame with or without stratum created by define_enroll_rate().

fail_rate

A fail_rate data frame with or without stratum created by define_fail_rate().

total_duration

Total follow-up from start of enrollment to data cutoff; this can be a single value or a vector of positive numbers.

ratio

Ratio of experimental to control randomization.

Examples

# Example: default
pw_info()

# Example: default with multiple analysis times (varying total_duration)
pw_info(total_duration = c(15, 30))

# Stratified population
enroll_rate <- define_enroll_rate(
  stratum = c(rep("Low", 2), rep("High", 3)),
  duration = c(2, 10, 4, 4, 8),
  rate = c(5, 10, 0, 3, 6)
)
fail_rate <- define_fail_rate(
  stratum = c(rep("Low", 2), rep("High", 2)),
  duration = c(1, Inf, 1, Inf),
  fail_rate = c(.1, .2, .3, .4),
  dropout_rate = .001,
  hr = c(.9, .75, .8, .6)
)
# Give results by change-points in the piecewise model
ahr(enroll_rate = enroll_rate, fail_rate = fail_rate, total_duration = c(15, 30))

# Same example, give results by strata and time period
pw_info(enroll_rate = enroll_rate, fail_rate = fail_rate, total_duration = c(15, 30))