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sim_gs_n: combine hetergenous test columns, fill missing with NAs #277

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Aug 20, 2024
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sim_gs_n: combine hetergenous test columns, fill missing with NAs #277

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8 changes: 6 additions & 2 deletions R/sim_gs_n.R
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Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,8 @@
#' @return A data frame summarizing the simulation ID, analysis date,
#' z statistics or p-values.
#'
#' @importFrom data.table rbindlist setDF
#'
#' @export
#'
#' @examplesIf requireNamespace("gsDesign2", quietly = TRUE)
Expand Down Expand Up @@ -325,13 +327,15 @@ sim_gs_n <- function(
)
ans_1sim_new <- convert_list_to_df_w_list_cols(ans_1sim_new)

# rbind simulation results for all IA(s) and FA in 1 simulation
ans_1sim <- rbind(ans_1sim, ans_1sim_new)
# bind rows of simulation results for all IA(s) and FA in 1 simulation
ans_1sim_list <- list(ans_1sim, ans_1sim_new)
ans_1sim <- rbindlist(ans_1sim_list, use.names = TRUE, fill = TRUE)

}

ans_1sim
}
setDF(ans)
return(ans)
}

Expand Down
52 changes: 32 additions & 20 deletions tests/testthat/test-unvalidated-sim_gs_n.R
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Original file line number Diff line number Diff line change
Expand Up @@ -348,14 +348,14 @@ test_that("WLR with fh(0, 0.5) test at IA1, WLR with mb(6, Inf) at IA2, and mile
fa_test <- create_test(milestone, ms_time = 10, test_type = "naive")

set.seed(2024)
# observed <- sim_gs_n(
# n_sim = 3,
# sample_size = 400,
# enroll_rate = enroll_rate,
# fail_rate = fail_rate,
# test = list(ia1 = ia1_test, ia2 = ia2_test, fa = fa_test),
# cut = cut
# )
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = list(ia1 = ia1_test, ia2 = ia2_test, fa = fa_test),
cut = cut
)

expected <- data.frame(
sim_id = rep(1:3, each = 3L),
Expand All @@ -379,9 +379,17 @@ test_that("WLR with fh(0, 0.5) test at IA1, WLR with mb(6, Inf) at IA2, and mile
2.66458078201881, 2.96576494908061, 1.1017919,
2.02623570402444, 2.14298279999738, 1.9969141,
2.49558219632314, 2.81323027566226, 0.9543971
),
info = c(
18.234728155604408, 154.73996276625465, NA, 17.323744020480003,
146.078846032117, NA, 15.524151518925096, 134.8967385215799, NA
),
info0 = c(
18.97777882184863, 157.11581663819095, NA, 17.488976711530597,
146.64084968485673, NA, 15.969731304813632, 136.27941618722392, NA
)
)
# expect_equal(observed, expected)
expect_equal(observed, expected)
})

test_that("MaxCombo (WLR-FH(0,0) + WLR-FH(0, 0.5))", {
Expand Down Expand Up @@ -502,15 +510,14 @@ test_that("sim_gs_n() can combine wlr(), rmst(), and milestone() tests", {
test_cut3 <- create_test(milestone, ms_time = 10, test_type = "naive")

set.seed(2024)
# observed <- sim_gs_n(
# n_sim = 3,
# sample_size = 400,
# enroll_rate = enroll_rate,
# fail_rate = fail_rate,
# test = list(test_cut1, test_cut2, test_cut3),
# cut = cut
# )

observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = list(test_cut1, test_cut2, test_cut3),
cut = cut
)
expected <- data.frame(
sim_id = rep(1:3, each = 3L),
method = rep(c("WLR", "RMST", "milestone"), 3),
Expand All @@ -533,9 +540,14 @@ test_that("sim_gs_n() can combine wlr(), rmst(), and milestone() tests", {
1.90987689210094, 1.40273642200249, 1.1017919,
1.74511717188905, 1.82220407393879, 1.9969141,
2.10969577332675, 1.80482023189919, 0.9543971
)
),
info = c(
60.307377049180324, NA, NA, 58.365957446808515, NA,
NA, 54.738738738738746, NA, NA
),
info0 = c(61, NA, NA, 58.75, NA, NA, 55.5, NA, NA)
)
# expect_equal(observed, expected)
expect_equal(observed, expected)
})

test_that("convert_list_to_df_w_list_cols() is robust to diverse input", {
Expand Down