MaxCombo p-value

Computes p-values for the MaxCombo test based on output from fh_weight(). This is still in an experimental stage and is intended for use with the sim_fixed_n() trial simulation routine. However, it can also be used to analyze clinical trial data such as that provided in the ADaM ADTTE format.

Usage

pvalue_maxcombo(
  z,
  algorithm = mvtnorm::GenzBretz(maxpts = 50000, abseps = 1e-05)
)

Arguments

z

A dataset output from fh_weight(); see examples.

algorithm

This is passed directly to the algorithm argument in mvtnorm::pmvnorm().

Value

A numeric p-value.

Examples

library(dplyr)

# Example 1
x <- sim_fixed_n(
  n_sim = 1,
  timing_type = 5,
  rho_gamma = data.frame(
    rho = c(0, 0, 1),
    gamma = c(0, 1, 1)
  )
)
#> Backend uses sequential processing.
#> Loading required package: foreach
#> Loading required package: future
#> 
#> Attaching package: ‘future’
#> The following object is masked from ‘package:survival’:
#> 
#>     cluster
head(x)
#>   event      ln_hr rho gamma         z        v1        v2        v3
#> 1   374 -0.3782851   0     0 -3.644545 1.0000000 0.8560315 0.9357919
#> 2   374 -0.3782851   0     1 -3.982620 0.8560315 1.0000000 0.9264503
#> 3   374 -0.3782851   1     1 -4.286398 0.9357919 0.9264503 1.0000000
#>                             cut duration sim
#> 1 Max(min follow-up, event cut) 76.61183   1
#> 2 Max(min follow-up, event cut) 76.61183   1
#> 3 Max(min follow-up, event cut) 76.61183   1
pvalue_maxcombo(x)
#> [1] 1.208958e-05

# Example 2
# Only use cuts for events, events + min follow-up
xx <- sim_fixed_n(
  n_sim = 100,
  timing_type = 5,
  rho_gamma = data.frame(
    rho = c(0, 0, 1),
    gamma = c(0, 1, 1)
  )
)
#> Backend uses sequential processing.
head(xx)
#>   event      ln_hr rho gamma         z        v1        v2        v3
#> 1   370 -0.5559926   0     0 -5.316363 1.0000000 0.8534282 0.9331543
#> 2   370 -0.5559926   0     1 -4.896380 0.8534282 1.0000000 0.9254183
#> 3   370 -0.5559926   1     1 -4.947177 0.9331543 0.9254183 1.0000000
#> 4   364 -0.1971851   0     0 -1.876825 1.0000000 0.8553223 0.9351107
#> 5   364 -0.1971851   0     1 -2.413346 0.8553223 1.0000000 0.9281533
#> 6   364 -0.1971851   1     1 -2.488439 0.9351107 0.9281533 1.0000000
#>                             cut duration sim
#> 1 Max(min follow-up, event cut) 72.63732   1
#> 2 Max(min follow-up, event cut) 72.63732   1
#> 3 Max(min follow-up, event cut) 72.63732   1
#> 4 Max(min follow-up, event cut) 74.87902   2
#> 5 Max(min follow-up, event cut) 74.87902   2
#> 6 Max(min follow-up, event cut) 74.87902   2

# MaxCombo power estimate for cutoff at max of targeted events, minimum follow-up
p <- xx |>
  group_by(sim) |>
  group_map(~ pvalue_maxcombo(.x)) |>
  unlist()
mean(p < .025)
#> [1] 0.96