"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"
"Diagnostics overview:"
" Model Distribution Prior x_cont              Prior x_fac3              max[error(MCMC)] max[error(MCMC)/SD] min(ESS) max(R-hat)"
"     1    gamma-aft Normal(0, 1) treatment contrast: Uniform(-0.1, 0.1)          0.00301               0.024     1808      1.003"
"     2  weibull-aft Normal(0, 1) treatment contrast: Uniform(-0.1, 0.1)          0.00096               0.012     6511      1.001"
"     3    lnorm-aft Normal(0, 1) treatment contrast: Uniform(-0.1, 0.1)          0.00113               0.013     5974      1.001"
"     4   llogis-aft Normal(0, 1) treatment contrast: Uniform(-0.1, 0.1)          0.00101               0.014     5198      1.001"
"     5    gamma-aft Normal(0, 1)         treatment contrast: Beta(3, 3)          0.00347               0.025     1610      1.002"
"     6  weibull-aft Normal(0, 1)         treatment contrast: Beta(3, 3)          0.00179               0.015     4305      1.001"
"     7    lnorm-aft Normal(0, 1)         treatment contrast: Beta(3, 3)          0.00203               0.016     3732      1.001"
"     8   llogis-aft Normal(0, 1)         treatment contrast: Beta(3, 3)          0.00187               0.016     4042      1.000"
