"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)"
""
"Robust Bayesian survival analysis"
"Distributions summary:"
"            Models Prior prob. Post. prob. Inclusion BF"
"gamma-aft      2/8       0.500       0.914       10.587"
"weibull-aft    2/8       0.167       0.084        0.457"
"lnorm-aft      2/8       0.167       0.000        0.000"
"llogis-aft     2/8       0.167       0.003        0.013"
""
"Components summary:"
"       Models Prior prob. Post. prob. Inclusion BF"
"x_fac3    4/8       0.500       0.189        0.234"
""
"Model-averaged estimates:"
"           Mean Median  0.025 0.975"
"x_cont    0.056  0.056 -0.081 0.193"
"x_fac3[B] 0.053  0.020 -0.094 0.421"
"x_fac3[C] 0.093  0.052 -0.086 0.534"
