"Call:"
"RoBMA(d = -d, se = d_se, effect_direction = \"negative\", model_type = \"PSMA\", "
"    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   1.041                                                       "
""
"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   0.960                                                              "
""
"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   1.054                                                       "
""
"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   1.458                                                                "
""
"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   2.495                                                              "
""
"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   3.184                                                                       "
""
"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   1.678                                          "
""
"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   0.587                                          "
""
"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   0.733                                          "
""
"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   0.991                                                       "
""
"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   0.842                                                              "
""
"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   1.077                                                       "
""
"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   1.348                                                                "
""
"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   2.732                                                              "
""
"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   3.208                                                                       "
""
"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   1.274                                          "
""
"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   1.442                                          "
""
"Parameter estimates:"
"     Mean    SD    lCI Median    uCI error(MCMC) error(MCMC)/SD   ESS R-hat"
"mu -0.481 0.223 -0.921 -0.480 -0.047     0.00221          0.010 10143 1.000"
"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)   -0.10                               tau ~ Spike(0)          "
" Post. prob.    0.013             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.275                                                       "
""
"Parameter estimates:"
"                Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            -0.405 0.221 -0.849 -0.401 0.010     0.00257          0.012 7436 1.000"
"omega[0,0.05]  1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.05,1]  0.540 0.264  0.084  0.542 0.975     0.00378          0.014 4852 1.000"
"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   0.960                                                              "
""
"Parameter estimates:"
"                  Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              -0.375 0.217 -0.817 -0.370 0.026     0.00255          0.012 7228 1.001"
"omega[0,0.05]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.05,0.1]  0.685 0.222  0.209  0.724 0.988     0.00352          0.016 3990 1.003"
"omega[0.1,1]     0.418 0.220  0.072  0.395 0.870     0.00316          0.014 4838 1.002"
"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   1.066                                                       "
""
"Parameter estimates:"
"                Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            -0.405 0.235 -0.869 -0.405 0.050     0.00278          0.012 7137 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]  0.582 0.259  0.099  0.599 0.981     0.00401          0.015 4169 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   1.050                                                                "
""
"Parameter estimates:"
"                    Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                -0.352 0.235 -0.819 -0.346 0.094     0.00287          0.012 6687 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]  0.676 0.226  0.191  0.712 0.987     0.00366          0.016 3808 1.000"
"omega[0.05,1]      0.396 0.223  0.053  0.370 0.856     0.00346          0.016 4159 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)    0.24                                   tau ~ Spike(0)             "
" Post. prob.    0.019             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.798                                                              "
""
"Parameter estimates:"
"                  Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              -0.364 0.254 -0.845 -0.369 0.148     0.00299          0.012 7216 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]  0.692 0.220  0.205  0.728 0.988     0.00349          0.016 3965 1.000"
"omega[0.5,1]     0.304 0.232  0.009  0.255 0.823     0.00381          0.016 3699 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   1.851                                                                       "
""
"Parameter estimates:"
"                    Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                -0.327 0.252 -0.807 -0.331 0.180     0.00316          0.013 6357 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]  0.752 0.192  0.300  0.796 0.992     0.00332          0.017 3359 1.001"
"omega[0.05,0.5]    0.520 0.215  0.126  0.523 0.913     0.00360          0.017 3567 1.001"
"omega[0.5,1]       0.231 0.190  0.006  0.183 0.685     0.00325          0.017 3425 1.001"
"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   0.773                                          "
""
"Parameter estimates:"
"      Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  -0.235 0.313 -0.784 -0.262 0.451     0.00627          0.020 2501 1.002"
"PET  0.681 0.607  0.024  0.512 2.295     0.01375          0.023 1947 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)   -1.52                tau ~ Spike(0)            "
" Post. prob.    0.010              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.300                                          "
""
"Parameter estimates:"
"        Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu    -0.287 0.275 -0.794 -0.297 0.282     0.00424          0.015 4195 1.000"
"PEESE  1.286 1.059  0.045  1.023 3.937     0.01859          0.018 3248 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)   -0.40                   tau ~ InvGamma(1, 0.15)"
" Post. prob.    0.118                                          "
" Inclusion BF   0.938                                          "
""
"Parameter estimates:"
"      Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  -0.449 0.278 -0.985 -0.451 0.105     0.00321          0.012 7498 1.001"
"tau  0.210 0.227  0.037  0.146 0.743     0.00272          0.012 6922 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)   -0.53                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.009             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.830                                                       "
""
"Parameter estimates:"
"                Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            -0.383 0.262 -0.905 -0.382 0.120     0.00302          0.012 7509 1.000"
"tau            0.190 0.181  0.036  0.138 0.656     0.00212          0.012 7276 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]  0.560 0.260  0.097  0.569 0.979     0.00380          0.015 4697 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   0.618                                                              "
""
"Parameter estimates:"
"                  Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              -0.357 0.256 -0.872 -0.354 0.116     0.00306          0.012 7033 1.000"
"tau              0.188 0.171  0.037  0.139 0.621     0.00214          0.013 6374 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]  0.699 0.214  0.231  0.734 0.988     0.00356          0.017 3606 1.000"
"omega[0.1,1]     0.428 0.219  0.080  0.408 0.873     0.00339          0.015 4168 1.001"
"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   0.743                                                       "
""
"Parameter estimates:"
"                Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            -0.354 0.286 -0.895 -0.358 0.215     0.00350          0.012 6657 1.000"
"tau            0.211 0.214  0.039  0.148 0.743     0.00251          0.012 7256 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]  0.583 0.258  0.100  0.604 0.980     0.00377          0.015 4675 1.001"
"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)   -0.65                                     tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.008             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.729                                                                "
""
"Parameter estimates:"
"                    Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                -0.304 0.284 -0.841 -0.309 0.272     0.00376          0.013 5705 1.000"
"tau                0.205 0.211  0.038  0.146 0.705     0.00251          0.012 7040 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]  0.682 0.224  0.202  0.719 0.988     0.00371          0.017 3654 1.001"
"omega[0.05,1]      0.401 0.225  0.056  0.376 0.861     0.00343          0.015 4312 1.000"
"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)    0.02                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.015             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.447                                                              "
""
"Parameter estimates:"
"                  Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              -0.251 0.370 -0.868 -0.285 0.589     0.00579          0.016 4075 1.000"
"tau              0.247 0.257  0.036  0.166 0.907     0.00374          0.015 4707 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]  0.688 0.221  0.204  0.726 0.988     0.00342          0.016 4147 1.001"
"omega[0.5,1]     0.281 0.228  0.006  0.222 0.799     0.00436          0.019 2730 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   1.480                                                                       "
""
"Parameter estimates:"
"                    Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                -0.217 0.367 -0.834 -0.246 0.607     0.00550          0.015 4442 1.000"
"tau                0.242 0.257  0.039  0.164 0.881     0.00366          0.014 4944 1.001"
"omega[0,0.025]     1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.025,0.05]  0.751 0.191  0.308  0.791 0.992     0.00310          0.016 3793 1.001"
"omega[0.05,0.5]    0.524 0.213  0.133  0.528 0.908     0.00340          0.016 3908 1.001"
"omega[0.5,1]       0.211 0.186  0.004  0.156 0.669     0.00338          0.018 3035 1.000"
"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   0.581                                          "
""
"Parameter estimates:"
"      Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  -0.179 0.373 -0.808 -0.212 0.674     0.00741          0.020 2540 1.000"
"tau  0.227 0.238  0.038  0.154 0.842     0.00299          0.013 6359 1.000"
"PET  0.742 0.675  0.023  0.565 2.525     0.01545          0.023 1912 1.000"
"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    -0.196 0.363 -0.803 -0.230 0.611     0.00635          0.018 3259 1.002"
"tau    0.253 0.278  0.038  0.165 0.964     0.00398          0.014 4879 1.001"
"PEESE  1.550 1.302  0.054  1.232 4.834     0.02397          0.018 2948 1.002"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
