gs_design_ahr: Group sequential design using average hazard ratio under...
In keaven/gsdmvn: Group sequential design with non-constant effect

Description Usage Arguments Details Value Examples

Group sequential design using average hazard ratio under non-proportional hazards

gs_design_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,
  alpha = 0.025,
  beta = 0.1,
  IF = NULL,
  analysisTimes = 36,
  binding = FALSE,
  upper = gs_b,
  upar = gsDesign(k = 3, test.type = 1, n.I = c(0.25, 0.75, 1), sfu = sfLDOF, sfupar =
    NULL)$upper$bound,
  lower = gs_b,
  lpar = c(qnorm(0.1), -Inf, -Inf),
  h1_spending = TRUE,
  test_upper = TRUE,
  test_lower = TRUE,
  r = 18,
  tol = 1e-06
)

`enrollRates`	enrollment rates
`failRates`	failure and dropout rates
`ratio`	Experimental:Control randomization ratio (not yet implemented)
`alpha`	One-sided Type I error
`beta`	Type II error
`IF`	Targeted information fraction at each analysis
`analysisTimes`	Minimum time of analysis
`binding`	indicator of whether futility bound is binding; default of FALSE is recommended
`upper`	Function to compute upper bound
`upar`	Parameter passed to `upper()`
`lower`	Function to compute lower bound
`lpar`	Parameter passed to `lower()`
`h1_spending`	Indicator that lower bound to be set by spending under alternate hypothesis (input `failRates`) if spending is used for lower bound
`test_upper`	indicator of which analyses should include an upper (efficacy) bound; single value of TRUE (default) indicates all analyses; otherwise, a logical vector of the same length as `info` should indicate which analyses will have an efficacy bound
`test_lower`	indicator of which analyses should include an lower bound; single value of TRUE (default) indicates all analyses; single value FALSE indicated no lower bound; otherwise, a logical vector of the same length as `info` should indicate which analyses will have a lower bound
`r`	Integer, at least 2; default of 18 recommended by Jennison and Turnbull
`tol`	Tolerance parameter for boundary convergence (on Z-scale)

Need to be added

a tibble with columns Analysis, Bound, Z, Probability, theta, Time, AHR, Events

library(gsDesign)
library(gsDesign2)
library(dplyr)
# call with defaults
gs_design_ahr()

# Single analysis
gs_design_ahr(analysisTimes = 40)

# Multiple analysisTimes
gs_design_ahr(analysisTimes = c(12,24,36))

# Specified information fraction
gs_design_ahr(IF = c(.25,.75,1), analysisTimes = 36)

# multiple analysis times & IF
# driven by times
gs_design_ahr(IF = c(.25,.75,1), analysisTimes = c(12,25,36))
# driven by IF
gs_design_ahr(IF = c(1/3, .8, 1), analysisTimes = c(12,25,36))

# 2-sided symmetric design with O'Brien-Fleming spending
gs_design_ahr(analysisTimes = c(12, 24, 36),
              binding = TRUE,
              upper = gs_spending_bound,
              upar = list(sf = gsDesign::sfLDOF, total_spend = 0.025, param = NULL, timing = NULL, theta=0),
              lower = gs_spending_bound,
              lpar = list(sf = gsDesign::sfLDOF, total_spend = 0.025, param = NULL, timing = NULL, theta=0),
              h1_spending = FALSE)