"Call:"
"RoBMA(d = d, se = d_se, model_type = \"2w\", parallel = TRUE, seed = 1)"
""
"Robust Bayesian meta-analysis                                                               "
" Model              1             Parameter prior distributions"
" Prior prob.    0.125                             mu ~ Spike(0)"
" log(marglik)   -0.83                            tau ~ Spike(0)"
" Post. prob.    0.082                                          "
" Inclusion BF   0.625                                          "
""
"Parameter estimates:"
"[1] Mean           SD             lCI            Median         uCI            error(MCMC)    error(MCMC)/SD ESS            R-hat         "
"<0 rows> (or 0-length row.names)"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                            "
" Model              2                          Parameter prior distributions"
" Prior prob.    0.062                                mu ~ Spike(0)          "
" log(marglik)   -0.30                               tau ~ Spike(0)          "
" Post. prob.    0.070             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.127                                                       "
""
"Parameter estimates:"
"               Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"omega[0,0.05] 1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,1] 0.428 0.271 0.045  0.381 0.958     0.00414          0.015 4300 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                   "
" Model              3                                 Parameter prior distributions"
" Prior prob.    0.062                                    mu ~ Spike(0)             "
" log(marglik)   -0.38                                   tau ~ Spike(0)             "
" Post. prob.    0.064             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.034                                                              "
""
"Parameter estimates:"
"                 Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"omega[0,0.05]   1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,0.1] 0.631 0.237 0.158  0.656 0.983     0.00371          0.016 4094 1.000"
"omega[0.1,1]    0.323 0.204 0.045  0.281 0.793     0.00297          0.015 4721 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                               "
" Model              4             Parameter prior distributions"
" Prior prob.    0.125                    mu ~ Spike(0)         "
" log(marglik)   -0.62                   tau ~ InvGamma(1, 0.15)"
" Post. prob.    0.102                                          "
" Inclusion BF   0.794                                          "
""
"Parameter estimates:"
"     Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau 0.296 0.271 0.044  0.219 0.987     0.00301          0.011 8101 1.004"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                            "
" Model              5                          Parameter prior distributions"
" Prior prob.    0.062                                mu ~ Spike(0)          "
" log(marglik)   -0.35                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.067             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.070                                                       "
""
"Parameter estimates:"
"               Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau           0.227 0.195 0.039  0.173 0.731     0.00234          0.012 6897 1.000"
"omega[0,0.05] 1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,1] 0.478 0.271 0.061  0.453 0.969     0.00403          0.015 4515 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                   "
" Model              6                                 Parameter prior distributions"
" Prior prob.    0.062                                    mu ~ Spike(0)             "
" log(marglik)   -0.51                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.057             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.901                                                              "
""
"Parameter estimates:"
"                 Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau             0.216 0.180 0.041  0.165 0.684     0.00205          0.011 7706 1.001"
"omega[0,0.05]   1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,0.1] 0.653 0.233 0.174  0.685 0.985     0.00369          0.016 4000 1.000"
"omega[0.1,1]    0.368 0.217 0.054  0.336 0.845     0.00320          0.015 4615 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                               "
" Model              7             Parameter prior distributions"
" Prior prob.    0.125                         mu ~ Normal(0, 1)"
" log(marglik)   -0.03                        tau ~ Spike(0)    "
" Post. prob.    0.184                                          "
" Inclusion BF   1.574                                          "
""
"Parameter estimates:"
"    Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD   ESS R-hat"
"mu 0.479 0.221 0.040  0.479 0.918     0.00218          0.010 10339 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                            "
" Model              8                          Parameter prior distributions"
" Prior prob.    0.062                                mu ~ Normal(0, 1)      "
" log(marglik)   -0.11                               tau ~ Spike(0)          "
" Post. prob.    0.085             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.393                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.405 0.224 -0.018  0.399 0.860     0.00250          0.011 8062 1.000"
"omega[0,0.05] 1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,1] 0.547 0.261  0.086  0.554 0.974     0.00369          0.014 5032 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                   "
" Model              9                                 Parameter prior distributions"
" Prior prob.    0.062                                    mu ~ Normal(0, 1)         "
" log(marglik)   -0.38                                   tau ~ Spike(0)             "
" Post. prob.    0.065             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.037                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.377 0.218 -0.026  0.371 0.820     0.00242          0.011 8100 1.000"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,0.1] 0.687 0.221  0.206  0.725 0.989     0.00349          0.016 4028 1.000"
"omega[0.1,1]    0.420 0.219  0.071  0.399 0.862     0.00308          0.014 5071 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                               "
" Model             10             Parameter prior distributions"
" Prior prob.    0.125                    mu ~ Normal(0, 1)     "
" log(marglik)   -0.39                   tau ~ InvGamma(1, 0.15)"
" Post. prob.    0.128                                          "
" Inclusion BF   1.024                                          "
""
"Parameter estimates:"
"     Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  0.452 0.280 -0.110  0.457 0.982     0.00316          0.011 7807 1.000"
"tau 0.211 0.232  0.037  0.146 0.765     0.00279          0.012 6929 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                            "
" Model             11                          Parameter prior distributions"
" Prior prob.    0.062                                mu ~ Normal(0, 1)      "
" log(marglik)   -0.52                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.056             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.892                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.381 0.257 -0.108  0.379 0.880     0.00281          0.011 8369 1.000"
"tau           0.190 0.179  0.036  0.139 0.627     0.00206          0.011 7577 1.000"
"omega[0,0.05] 1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,1] 0.565 0.259  0.099  0.574 0.978     0.00379          0.015 4684 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                   "
" Model             12                                 Parameter prior distributions"
" Prior prob.    0.062                                    mu ~ Normal(0, 1)         "
" log(marglik)   -0.82                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.042             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.651                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.358 0.248 -0.106  0.349 0.861     0.00274          0.011 8164 1.001"
"tau             0.184 0.164  0.036  0.136 0.609     0.00190          0.012 7394 1.000"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.05,0.1] 0.703 0.213  0.235  0.740 0.989     0.00331          0.016 4150 1.000"
"omega[0.1,1]    0.433 0.219  0.081  0.415 0.868     0.00317          0.014 4780 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
