simtrial: Clinical Trial Simulation

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#
#  This file is part of the simtrial program.
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#' Simulated survival dataset with delayed treatment effect
#'
#' Magirr and Burman (2019) considered several scenarios for their
#' modestly weighted logrank test.
#' One of these had a delayed treatment effect with a hazard ratio
#' of 1 for 6 months followed by a hazard ratio of 1/2 thereafter.
#' The scenario enrolled 200 patients uniformly over 12 months and
#' cut data for analysis 36 months after enrollment was opened.
#' This dataset was generated by the [sim_pw_surv()] function
#' under the above scenario.
#'
#' @format
#' A data frame with 200 rows and 4 columns:
#' - `tte`: Time to event.
#'
#' @references
#' Magirr, Dominic, and Carl‐Fredrik Burman. 2019.
#' "Modestly weighted logrank tests."
#' _Statistics in Medicine_ 38 (20): 3782--3790.
#'
#' @examples
#' library(survival)
#'
#' fit <- survfit(Surv(tte, event) ~ treatment, data = mb_delayed_effect)
#'
#' # Plot survival
#' plot(fit, lty = 1:2)
#' legend("topright", legend = c("control", "experimental"), lty = 1:2)
#'
#' # Set up time, event, number of event dataset for testing
#' # with arbitrary weights
#' ten <- mb_delayed_effect |> counting_process(arm = "experimental")
#' head(ten)
#'
#' # MaxCombo with logrank, FH(0,1), FH(1,1)
#' mb_delayed_effect |>
#'   maxcombo(rho = c(0, 0, 1), gamma = c(0, 1, 1), return_corr = TRUE)
#'
#' # Generate another dataset
#' ds <- sim_pw_surv(
#'   n = 200,
#'   enroll_rate = data.frame(rate = 200 / 12, duration = 12),
#'   fail_rate = data.frame(
#'     stratum = c("All", "All", "All"),
#'     period = c(1, 1, 2),
#'     treatment = c("control", "experimental", "experimental"),
#'     duration = c(42, 6, 36),
#'     rate = c(log(2) / 15, log(2) / 15, log(2) / 15 * 0.6)
#'   ),
#'   dropout_rate = data.frame(
#'     stratum = c("All", "All"),
#'     period = c(1, 1),
#'     treatment = c("control", "experimental"),
#'     duration = c(42, 42),
#'     rate = c(0, 0)
#'   )
#' )
#' # Cut data at 24 months after final enrollment
#' mb_delayed_effect_2 <- ds |> cut_data_by_date(max(ds$enroll_time) + 24)
"mb_delayed_effect"