library("survatr")
set.seed(2)
n_id <- 40L
K <- 5L
pp <- data.frame(
id = rep(seq_len(n_id), each = K),
t = rep(seq_len(K), times = n_id),
A = rep(rbinom(n_id, 1L, 0.5), each = K),
Y = rbinom(n_id * K, 1L, 0.1)
)
fit <- surv_fit(pp, "Y", "A", ~1, "id", "t", time_formula = ~ factor(t))
res <- contrast(
fit,
interventions = list(a1 = causatr::static(1), a0 = causatr::static(0)),
times = 1:5,
type = "risk_difference"
)
forrest(res, t_ref = 5)