"Call:"
"RoBSA(formula = Surv(time = time, event = event) ~ 1, data = df, "
"    parallel = TRUE, seed = 1, rescale_data = TRUE)"
""
"Robust Bayesian meta-analysis                                                                 "
" Model                1             Parameter prior distributions"
" Prior prob.      0.200                  intercept ~ Normal(0, 5)"
" log(marglik)   -317.64                                          "
" Post. prob.      0.852                                          "
" Inclusion BF    23.061                                          "
""
"Parameter estimates:"
"           Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"intercept 0.539 0.069 0.404  0.538 0.677     0.00072          0.010 9271 1.000"
""
"                                                                    "
" Model                2                Parameter prior distributions"
" Prior prob.      0.200             intercept ~ Normal(0, 5)        "
" log(marglik)   -320.25                   aux ~ Normal(0, 1)[0, Inf]"
" Post. prob.      0.062                                             "
" Inclusion BF     0.266                                             "
""
"Parameter estimates:"
"           Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"intercept 0.544 0.072 0.409  0.542 0.691     0.00075          0.010 9441 1.000"
"aux       0.977 0.054 0.873  0.976 1.083     0.00059          0.011 8391 1.001"
""
"                                                                    "
" Model                3                Parameter prior distributions"
" Prior prob.      0.200             intercept ~ Normal(0, 5)        "
" log(marglik)   -329.97                   aux ~ Normal(0, 1)[0, Inf]"
" Post. prob.      0.000                                             "
" Inclusion BF     0.000                                             "
""
"Parameter estimates:"
"           Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"intercept 0.078 0.093 -0.102  0.076 0.265     0.00106          0.011 7698 1.001"
"aux       1.471 0.074  1.334  1.468 1.623     0.00086          0.012 7440 1.000"
""
"                                                                    "
" Model                4                Parameter prior distributions"
" Prior prob.      0.200             intercept ~ Normal(0, 5)        "
" log(marglik)   -324.44                   aux ~ Normal(0, 1)[0, Inf]"
" Post. prob.      0.001                                             "
" Inclusion BF     0.004                                             "
""
"Parameter estimates:"
"           Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"intercept 0.102 0.085 -0.063  0.101 0.274     0.00096          0.011 7924 1.001"
"aux       1.242 0.071  1.107  1.241 1.383     0.00079          0.011 8023 1.000"
""
"                                                                    "
" Model                5                Parameter prior distributions"
" Prior prob.      0.200             intercept ~ Normal(0, 5)        "
" log(marglik)   -319.95                   aux ~ Normal(0, 1)[0, Inf]"
" Post. prob.      0.085                                             "
" Inclusion BF     0.370                                             "
""
"Parameter estimates:"
"           Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"intercept 0.575 0.127 0.334  0.573 0.833     0.00303          0.024 1746 1.001"
"aux       0.976 0.077 0.835  0.974 1.135     0.00184          0.024 1724 1.000"
