library("survatr")
set.seed(4)
n_id <- 40L; K <- 3L
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),
L = rep(rnorm(n_id), each = K),
Y = rbinom(n_id * K, 1L, 0.05)
)
fit <- surv_fit(pp, "Y", "A", ~L, "id", "t", time_formula = ~1)
print(diagnose(fit))<survatr_diag>
Positivity: 3 periods, hazards [0.0091, 0.2397]
Balance: 1 variable(s), SMD range [-0.265, -0.177]
Censoring: (no censoring column supplied)