"Call:"
"RoBMA(d = d, se = d_se, 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.    0.076                                          "
" Inclusion BF   0.578                                          "
""
"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.    0.010                                mu ~ Spike(0)          "
" log(marglik)   -0.30                               tau ~ Spike(0)          "
" Post. prob.    0.011             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.040                                                       "
""
"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.    0.010                                    mu ~ Spike(0)             "
" log(marglik)   -0.38                                   tau ~ Spike(0)             "
" Post. prob.    0.010             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.959                                                              "
""
"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.    0.010                                mu ~ Spike(0)          "
" log(marglik)   -0.29                               tau ~ Spike(0)          "
" Post. prob.    0.011             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.053                                                       "
""
"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] 0.421 0.271 0.044  0.372 0.957     0.00415          0.015 4248 1.001"
"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.    0.010                                      mu ~ Spike(0)             "
" log(marglik)    0.03                                     tau ~ Spike(0)             "
" Post. prob.    0.015             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.457                                                                "
""
"Parameter estimates:"
"                   Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"omega[0,0.025]    1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.025,0.05] 0.606 0.249 0.126  0.627 0.982     0.00410          0.016 3679 1.000"
"omega[0.05,1]     0.271 0.203 0.028  0.216 0.776     0.00339          0.017 3576 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.    0.010                                    mu ~ Spike(0)             "
" log(marglik)    0.56                                   tau ~ Spike(0)             "
" Post. prob.    0.026             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   2.493                                                              "
""
"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[0.05,0.5] 0.616 0.243 0.145  0.639 0.984     0.00377          0.016 4138 1.000"
"omega[0.5,1]    0.210 0.192 0.005  0.150 0.710     0.00347          0.018 3065 1.000"
"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.    0.010                                          mu ~ Spike(0)                "
" log(marglik)    0.80                                         tau ~ Spike(0)                "
" Post. prob.    0.032             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   3.181                                                                       "
""
"Parameter estimates:"
"                   Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"omega[0,0.025]    1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.025,0.05] 0.707 0.211 0.243  0.745 0.988     0.00343          0.016 3774 1.000"
"omega[0.05,0.5]   0.446 0.216 0.090  0.429 0.877     0.00341          0.016 4026 1.002"
"omega[0.5,1]      0.153 0.152 0.003  0.103 0.571     0.00326          0.021 2187 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.    0.031                 mu ~ Spike(0)            "
" log(marglik)    0.16                tau ~ Spike(0)            "
" Post. prob.    0.051                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   1.676                                          "
""
"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              9             Parameter prior distributions"
" Prior prob.    0.031                 mu ~ Spike(0)            "
" log(marglik)   -0.86                tau ~ Spike(0)            "
" Post. prob.    0.019              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.586                                          "
""
"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             10             Parameter prior distributions"
" Prior prob.    0.125                    mu ~ Spike(0)         "
" log(marglik)   -0.62                   tau ~ InvGamma(1, 0.15)"
" Post. prob.    0.095                                          "
" Inclusion BF   0.732                                          "
""
"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             11                          Parameter prior distributions"
" Prior prob.    0.010                                mu ~ Spike(0)          "
" log(marglik)   -0.35                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.010             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.990                                                       "
""
"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             12                                 Parameter prior distributions"
" Prior prob.    0.010                                    mu ~ Spike(0)             "
" log(marglik)   -0.51                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.009             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.841                                                              "
""
"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             13                          Parameter prior distributions"
" Prior prob.    0.010                                mu ~ Spike(0)          "
" log(marglik)   -0.27                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.011             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.076                                                       "
""
"Parameter estimates:"
"               Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau           0.245 0.213 0.039  0.185 0.788     0.00246          0.012 7507 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] 0.462 0.270 0.055  0.428 0.962     0.00404          0.015 4475 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                     "
" Model             14                                   Parameter prior distributions"
" Prior prob.    0.010                                      mu ~ Spike(0)             "
" log(marglik)   -0.04                                     tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.014             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.347                                                                "
""
"Parameter estimates:"
"                   Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau               0.228 0.195 0.040  0.171 0.730     0.00230          0.012 7133 1.000"
"omega[0,0.025]    1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.025,0.05] 0.625 0.243 0.144  0.655 0.984     0.00397          0.016 3744 1.000"
"omega[0.05,1]     0.306 0.208 0.035  0.259 0.793     0.00319          0.015 4251 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                   "
" Model             15                                 Parameter prior distributions"
" Prior prob.    0.010                                    mu ~ Spike(0)             "
" log(marglik)    0.65                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.028             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   2.729                                                              "
""
"Parameter estimates:"
"                 Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau             0.259 0.235 0.042  0.194 0.851     0.00270          0.011 7566 1.001"
"omega[0,0.05]   1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,0.5] 0.644 0.237 0.165  0.673 0.987     0.00379          0.016 3907 1.001"
"omega[0.5,1]    0.222 0.200 0.006  0.160 0.742     0.00381          0.019 2749 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                            "
" Model             16                                          Parameter prior distributions"
" Prior prob.    0.010                                          mu ~ Spike(0)                "
" log(marglik)    0.80                                         tau ~ InvGamma(1, 0.15)       "
" Post. prob.    0.033             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   3.205                                                                       "
""
"Parameter estimates:"
"                   Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau               0.243 0.215 0.040  0.184 0.773     0.00240          0.011 8021 1.000"
"omega[0,0.025]    1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.025,0.05] 0.731 0.200 0.275  0.772 0.991     0.00324          0.016 3823 1.003"
"omega[0.05,0.5]   0.478 0.217 0.109  0.467 0.894     0.00355          0.016 3721 1.001"
"omega[0.5,1]      0.167 0.158 0.004  0.118 0.588     0.00295          0.019 2884 1.003"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                               "
" Model             17             Parameter prior distributions"
" Prior prob.    0.031                 mu ~ Spike(0)            "
" log(marglik)   -0.11                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.039                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   1.272                                          "
""
"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             18             Parameter prior distributions"
" Prior prob.    0.031                 mu ~ Spike(0)            "
" log(marglik)   -0.97                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.017              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.526                                          "
""
"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             19             Parameter prior distributions"
" Prior prob.    0.125                         mu ~ Normal(0, 1)"
" log(marglik)   -0.03                        tau ~ Spike(0)    "
" Post. prob.    0.171                                          "
" Inclusion BF   1.440                                          "
""
"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             20                          Parameter prior distributions"
" Prior prob.    0.010                                mu ~ Normal(0, 1)      "
" log(marglik)   -0.11                               tau ~ Spike(0)          "
" Post. prob.    0.013             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.267                                                       "
""
"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             21                                 Parameter prior distributions"
" Prior prob.    0.010                                    mu ~ Normal(0, 1)         "
" log(marglik)   -0.38                                   tau ~ Spike(0)             "
" Post. prob.    0.010             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.962                                                              "
""
"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             22                          Parameter prior distributions"
" Prior prob.    0.010                                mu ~ Normal(0, 1)      "
" log(marglik)   -0.28                               tau ~ Spike(0)          "
" Post. prob.    0.011             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.065                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.392 0.231 -0.057  0.393 0.843     0.00259          0.011 7914 1.001"
"omega[0,0.05] 1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,1] 0.581 0.258  0.097  0.600 0.981     0.00385          0.015 4482 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                     "
" Model             23                                   Parameter prior distributions"
" Prior prob.    0.010                                      mu ~ Normal(0, 1)         "
" log(marglik)   -0.29                                     tau ~ Spike(0)             "
" Post. prob.    0.011             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.053                                                                "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.351 0.232 -0.091  0.347 0.805     0.00281          0.012 6813 1.000"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.025,0.05] 0.683 0.225  0.198  0.722 0.988     0.00359          0.016 3930 1.000"
"omega[0.05,1]     0.401 0.224  0.054  0.377 0.865     0.00344          0.015 4258 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                   "
" Model             24                                 Parameter prior distributions"
" Prior prob.    0.010                                    mu ~ Normal(0, 1)         "
" log(marglik)    0.23                                   tau ~ Spike(0)             "
" Post. prob.    0.018             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.787                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.359 0.252 -0.151  0.365 0.844     0.00299          0.012 7094 1.000"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.05,0.5] 0.690 0.221  0.211  0.726 0.989     0.00337          0.015 4289 1.000"
"omega[0.5,1]    0.296 0.227  0.008  0.246 0.813     0.00387          0.017 3447 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                            "
" Model             25                                          Parameter prior distributions"
" Prior prob.    0.010                                          mu ~ Normal(0, 1)            "
" log(marglik)    0.27                                         tau ~ Spike(0)                "
" Post. prob.    0.019             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   1.859                                                                       "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.325 0.255 -0.173  0.325 0.823     0.00305          0.012 6970 1.000"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.025,0.05] 0.748 0.191  0.299  0.789 0.991     0.00321          0.017 3557 1.000"
"omega[0.05,0.5]   0.521 0.214  0.125  0.520 0.911     0.00352          0.016 3688 1.000"
"omega[0.5,1]      0.227 0.188  0.006  0.178 0.687     0.00334          0.018 3182 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                               "
" Model             26             Parameter prior distributions"
" Prior prob.    0.031                 mu ~ Normal(0, 1)        "
" log(marglik)   -0.59                tau ~ Spike(0)            "
" Post. prob.    0.024                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   0.771                                          "
""
"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             27             Parameter prior distributions"
" Prior prob.    0.031                 mu ~ Normal(0, 1)        "
" log(marglik)   -1.53                tau ~ Spike(0)            "
" Post. prob.    0.010              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.298                                          "
""
"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             28             Parameter prior distributions"
" Prior prob.    0.125                    mu ~ Normal(0, 1)     "
" log(marglik)   -0.39                   tau ~ InvGamma(1, 0.15)"
" Post. prob.    0.119                                          "
" Inclusion BF   0.943                                          "
""
"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             29                          Parameter prior distributions"
" Prior prob.    0.010                                mu ~ Normal(0, 1)      "
" log(marglik)   -0.52                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.009             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.834                                                       "
""
"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             30                                 Parameter prior distributions"
" Prior prob.    0.010                                    mu ~ Normal(0, 1)         "
" log(marglik)   -0.82                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.006             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.616                                                              "
""
"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)."
""
"                                                                            "
" Model             31                          Parameter prior distributions"
" Prior prob.    0.010                                mu ~ Normal(0, 1)      "
" log(marglik)   -0.63                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.008             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.748                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.359 0.288 -0.224  0.365 0.911     0.00362          0.013 6336 1.000"
"tau           0.210 0.203  0.039  0.148 0.749     0.00244          0.012 6925 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] 0.580 0.259  0.095  0.595 0.981     0.00382          0.015 4610 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                     "
" Model             32                                   Parameter prior distributions"
" Prior prob.    0.010                                      mu ~ Normal(0, 1)         "
" log(marglik)   -0.66                                     tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.008             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.726                                                                "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.298 0.293 -0.307  0.304 0.856     0.00382          0.013 5883 1.001"
"tau               0.204 0.198  0.037  0.144 0.710     0.00253          0.013 6104 1.001"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.025,0.05] 0.679 0.223  0.195  0.712 0.988     0.00353          0.016 3978 1.001"
"omega[0.05,1]     0.395 0.222  0.051  0.368 0.853     0.00331          0.015 4500 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                   "
" Model             33                                 Parameter prior distributions"
" Prior prob.    0.010                                    mu ~ Normal(0, 1)         "
" log(marglik)    0.03                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.015             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.458                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.248 0.375 -0.616  0.285 0.858     0.00607          0.016 3830 1.000"
"tau             0.249 0.275  0.039  0.164 0.953     0.00407          0.015 4571 1.000"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,0.5] 0.697 0.219  0.218  0.738 0.989     0.00352          0.016 3886 1.002"
"omega[0.5,1]    0.282 0.230  0.006  0.226 0.814     0.00433          0.019 2819 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                            "
" Model             34                                          Parameter prior distributions"
" Prior prob.    0.010                                          mu ~ Normal(0, 1)            "
" log(marglik)    0.05                                         tau ~ InvGamma(1, 0.15)       "
" Post. prob.    0.015             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   1.485                                                                       "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.214 0.360 -0.625  0.242 0.835     0.00557          0.015 4178 1.001"
"tau               0.241 0.241  0.037  0.166 0.853     0.00336          0.014 5128 1.001"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.025,0.05] 0.746 0.194  0.295  0.788 0.991     0.00317          0.016 3731 1.000"
"omega[0.05,0.5]   0.517 0.214  0.124  0.518 0.902     0.00341          0.016 3915 1.000"
"omega[0.5,1]      0.211 0.183  0.005  0.159 0.664     0.00337          0.018 2954 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                               "
" Model             35             Parameter prior distributions"
" Prior prob.    0.031                 mu ~ Normal(0, 1)        "
" log(marglik)   -0.87                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.018                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   0.582                                          "
""
"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             36             Parameter prior distributions"
" Prior prob.    0.031                 mu ~ Normal(0, 1)        "
" log(marglik)   -1.71                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.008              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.247                                          "
""
"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)."
