"Call:"
"RoBSA(formula = Surv(time = time, event = event) ~ x_cont + x_fac3, "
"    data = df, priors = list(x_fac3 = list(alt = prior_factor(\"beta\", "
"        list(3, 3), contrast = \"treatment\"), null = prior_factor(\"uniform\", "
"        list(-0.1, 0.1), contrast = \"treatment\"))), test_predictors = \"x_fac3\", "
"    distributions = c(\"gamma-aft\", \"weibull-aft\", \"lnorm-aft\", "
"        \"llogis-aft\"), distributions_weights = c(3, 1, 1, 1), "
"    prior_intercept = list(`gamma-aft` = prior(\"normal\", list(1, "
"        1)), `weibull-aft` = prior(\"normal\", list(2, 1)), `lnorm-aft` = prior(\"normal\", "
"        list(1, 3)), `llogis-aft` = prior(\"normal\", list(1, 4))), "
"    parallel = TRUE, seed = 6, rescale_data = TRUE)"
""
"Estimates:"
"    x_cont  x_fac3[B]  x_fac3[C] "
"0.05560707 0.05267116 0.09333443 "
