"Call:"
"RoBMA(d = d, se = d_se, model_type = \"PP\", 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.    0.092                                          "
" Inclusion BF   0.706                                          "
""
"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)    0.16                tau ~ Spike(0)            "
" Post. prob.    0.123                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   2.108                                          "
""
"Parameter estimates:"
"     Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"PET 0.899 0.485 0.091  0.859 1.945     0.00533          0.011 8257 1.001"
"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)   -0.86                tau ~ Spike(0)            "
" Post. prob.    0.045              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.700                                          "
""
"Parameter estimates:"
"       Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"PEESE 1.870 1.024 0.186  1.797 4.046     0.01077          0.011 9037 1.001"
"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.    0.114                                          "
" Inclusion BF   0.899                                          "
""
"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)   -0.11                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.095                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   1.569                                          "
""
"Parameter estimates:"
"     Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau 0.221 0.232 0.037  0.157 0.765     0.00250          0.011 8658 1.000"
"PET 0.852 0.520 0.069  0.787 2.004     0.00623          0.012 6972 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)   -0.97                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.040              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.626                                          "
""
"Parameter estimates:"
"       Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau   0.245 0.240 0.038  0.177 0.846     0.00259          0.011 8525 1.000"
"PEESE 1.829 1.112 0.142  1.715 4.326     0.01282          0.012 7523 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.    0.205                                          "
" Inclusion BF   1.805                                          "
""
"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)   -0.59                tau ~ Spike(0)            "
" Post. prob.    0.058                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   0.929                                          "
""
"Parameter estimates:"
"     Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  0.237 0.313 -0.458  0.260 0.784     0.00651          0.021 2307 1.000"
"PET 0.679 0.601  0.023  0.511 2.233     0.01348          0.022 1990 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)   -1.53                tau ~ Spike(0)            "
" Post. prob.    0.023              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.351                                          "
""
"Parameter estimates:"
"       Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu    0.291 0.268 -0.260  0.301 0.787     0.00397          0.015 4555 1.000"
"PEESE 1.268 1.019  0.049  1.036 3.819     0.01716          0.017 3522 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.    0.143                                          "
" Inclusion BF   1.164                                          "
""
"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)   -0.87                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.044                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   0.695                                          "
""
"Parameter estimates:"
"     Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  0.181 0.377 -0.682  0.215 0.828     0.00714          0.019 2783 1.003"
"tau 0.229 0.242  0.037  0.155 0.857     0.00292          0.012 6854 1.000"
"PET 0.730 0.646  0.023  0.556 2.439     0.01383          0.021 2184 1.002"
"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)   -1.71                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.019              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.291                                          "
""
"Parameter estimates:"
"       Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu    0.205 0.367 -0.617  0.235 0.845     0.00623          0.017 3482 1.001"
"tau   0.260 0.303  0.039  0.170 0.981     0.00455          0.015 4430 1.001"
"PEESE 1.554 1.324  0.050  1.233 4.823     0.02658          0.020 2480 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
