```
#' 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 `simtrial::sim_pw_surv()` function under the above scenario.
#'
#' @format A tibble with 200 rows and xx columns
#' \describe{
#' \item{tte}{time to event}
#' }
#' @examples
#' library(tidyr)
#' library(dplyr)
#' library(survival)
#' library(mvtnorm)
#' fit <- survfit(Surv(tte, event) ~ Treatment, data = MBdelayed)
#'
#' # 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 <- MBdelayed %>% counting_process(arm = "Experimental")
#' head(ten)
#'
#' # MaxCombo with logrank, FH(0,1), FH(1,1)
#' ten %>% tenFHcorr(rg = tibble(rho=c(0, 0, 1), gamma = c(0, 1, 1))) %>%
#' pvalue_maxcombo()
#'
#' # Magirr-Burman modestly down-weighted rank test with 6 month delay
#' # First, add weights
#' ten <- ten %>% mb_weight(6)
#' head(ten)
#'
#' # Now compute test based on these weights
#' ten %>% summarise(S = sum(o_minus_e*mb_weight),
#' V = sum(var_o_minus_e*mb_weight^2),
#' Z = S/sqrt(V)) %>%
#' mutate(p = pnorm(Z))
#'
#' # Create 0 weights for first 6 months
#' ten <- ten %>% mutate(w6 = 1 * (tte >= 6))
#' ten %>% summarise(S = sum(o_minus_e*w6),
#' V = sum(var_o_minus_e*w6^2),
#' Z = S/sqrt(V)) %>%
#' mutate(p=pnorm(Z))
#'
#' # Generate another dataset
#' ds <- sim_pw_surv(n = 200,
#' enroll_rate = tibble(rate = 200 / 12, duration = 12),
#' fail_rate = tribble(
#' ~Stratum, ~Period, ~Treatment, ~duration, ~rate,
#' "All", 1, "Control", 42, log(2) / 15,
#' "All", 1, "Experimental", 6, log(2) / 15,
#' "All", 2, "Experimental", 36, log(2) / 15 * 0.6),
#' dropoutRates = tribble(
#' ~Stratum, ~Period, ~Treatment, ~duration, ~rate,
#' "All", 1, "Control", 42, 0,
#' "All", 1, "Experimental", 42, 0)
#' )
#' # Cut data at 24 months after final enrollment
#' MBdelayed2 <- ds %>% cut_data_by_date(max(ds$enroll_time) + 24)
#' @references
#' Magirr, Dominic, and CarlāFredrik Burman.
#' "Modestly weighted logrank tests."
#' \emph{Statistics in Medicine} 38.20 (2019): 3782-3790.
#'
"MBdelayed"
```

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