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Check group sequential bounds

Source: R/check_gs_bound.R
check_gs_bound.Rd

Updates the group sequential design boundaries based on observed information and checks if boundaries have been crossed.

Usage

check_gs_bound(
  sim_results,
  design,
  info_scale = c("blinded", "unblinded"),
  info_col = NULL
)

Arguments

sim_results

Data frame of simulation results (from sim_gs_nbinom()).

design

The planning gsNB object.

info_scale

Character. Legacy selector for "blinded" (default) or "unblinded" information. Ignored when info_col is supplied.

info_col

Optional explicit column name containing the information metric to use for bounds, e.g. "info_unblinded_ml" or "info_blinded_mom".

Value

A data frame with added columns:

cross_upper

Logical, true if upper bound crossed (efficacy)

cross_lower

Logical, true if lower bound crossed (futility)

cross_harm

Logical, true if harm bound crossed (test.type 7 or 8)

Examples

design <- gsDesign::gsDesign(k = 2, n.fix = 100, test.type = 2, timing = c(0.5, 1))
sim_df <- data.frame(
  sim = c(1, 1, 2, 2),
  analysis = c(1, 2, 1, 2),
  z_stat = c(2.5, NA, -0.2, 2.2),
  blinded_info = c(50, 100, 50, 100),
  unblinded_info = c(50, 100, 50, 100)
)
check_gs_bound(sim_df, design)
#>   sim analysis z_stat blinded_info unblinded_info cross_upper cross_lower
#> 1   1        1    2.5           50             50       FALSE       FALSE
#> 2   1        2     NA          100            100       FALSE       FALSE
#> 3   2        1   -0.2           50             50       FALSE       FALSE
#> 4   2        2    2.2          100            100        TRUE       FALSE
#>   cross_harm
#> 1      FALSE
#> 2      FALSE
#> 3      FALSE
#> 4      FALSE
check_gs_bound(sim_df, design, info_col = "unblinded_info")
#>   sim analysis z_stat blinded_info unblinded_info cross_upper cross_lower
#> 1   1        1    2.5           50             50       FALSE       FALSE
#> 2   1        2     NA          100            100       FALSE       FALSE
#> 3   2        1   -0.2           50             50       FALSE       FALSE
#> 4   2        2    2.2          100            100        TRUE       FALSE
#>   cross_harm
#> 1      FALSE
#> 2      FALSE
#> 3      FALSE
#> 4      FALSE