library("survatr")
set.seed(1)
n_id <- 30L
K <- 4L
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))
print(fit)<survatr_fit>
Track: A
Estimator: gcomp
Family: binomial
Outcome: Y
Treatment: A
ID: id
Time: t
Censoring: none
N: 30 individuals, 120 PP rows (104 at risk)
Time grid: [1, 4] (4 unique times)