test_that("Models M1-M4 fit properly on simulated survival data with censoring", {
  set.seed(42)
  n <- 50
  x_mat <- matrix(rnorm(n), ncol = 1)
  colnames(x_mat) <- "X1"
  
  sim_dat <- r_alpha_power_reg(n = n, par = c(1.5, 1.1), x = x_mat, beta = 0.5,
                              model = "M1", cen_type = "right", cen_rate = 0.1)
  
  models <- c("M1", "M2", "M3", "M4")
  for (m in models) {
    fit <- fit_alpha_power(sim_dat$time, sim_dat$status, x = x_mat, model = m)
    expect_s3_class(fit, "alpha_power_fit")
    expect_true(is.finite(fit$logLik))
    expect_true(all(is.finite(fit$coefficients$Estimate)))
    
    res <- residuals_alpha_power(fit)
    expect_true(all(is.finite(res$cox_snell)))
    expect_true(all(is.finite(res$martingale)))
    expect_true(all(is.finite(res$deviance)))
    
    pred <- predict_alpha_power(fit, type = "survival")
    expect_true(all(is.finite(pred$survival) & pred$survival >= 0 & pred$survival <= 1))
  }
})

test_that("Formula interface alpha_power_hazard works cleanly", {
  set.seed(123)
  n <- 40
  df <- data.frame(
    time   = ralpha_power(n, alpha = 1.5, beta = 0.8),
    status = sample(c(1, 1, 1, 0), n, replace = TRUE),
    X1     = rnorm(n)
  )
  fit <- alpha_power_hazard(survival::Surv(time, status) ~ X1, data = df, model = "M1")
  expect_s3_class(fit, "alpha_power")
  
  s <- summary(fit)
  expect_s3_class(s, "summary.alpha_power")
  
  ci <- confint(fit)
  expect_true(all(is.finite(ci)))
})