"Call:"
"RoBMA(r = r, n = n, 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.    0.075                                          "
" Inclusion BF   0.565                                          "
""
"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)   -0.22                               tau ~ Spike(0)          "
" Post. prob.    0.012             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.108                                                       "
""
"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] 0.403 0.270 0.038  0.351 0.951     0.00442          0.016 3729 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.    0.010                                    mu ~ Spike(0)             "
" log(marglik)   -0.28                                   tau ~ Spike(0)             "
" Post. prob.    0.011             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.044                                                              "
""
"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 1.001"
"omega[0.05,0.1] 0.624 0.243 0.144  0.649 0.982     0.00384          0.016 3983 1.000"
"omega[0.1,1]    0.314 0.209 0.039  0.270 0.800     0.00331          0.016 3975 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)   -0.22                               tau ~ Spike(0)          "
" Post. prob.    0.011             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.100                                                       "
""
"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 1.001"
"omega[0.05,1] 0.412 0.274 0.039  0.356 0.959     0.00457          0.017 3593 1.000"
"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)    0.12                                     tau ~ Spike(0)             "
" Post. prob.    0.016             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.567                                                                "
""
"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] 0.605 0.251 0.121  0.627 0.982     0.00421          0.017 3555 1.000"
"omega[0.05,1]     0.261 0.202 0.023  0.205 0.758     0.00361          0.018 3126 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)    0.59                                   tau ~ Spike(0)             "
" Post. prob.    0.026             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   2.525                                                              "
""
"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] 0.609 0.247 0.135  0.628 0.983     0.00404          0.016 3718 1.000"
"omega[0.5,1]    0.206 0.192 0.005  0.145 0.711     0.00362          0.019 2808 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)    0.85                                         tau ~ Spike(0)                "
" Post. prob.    0.033             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   3.281                                                                       "
""
"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] 0.711 0.211 0.240  0.753 0.990     0.00348          0.016 3679 1.000"
"omega[0.05,0.5]   0.440 0.220 0.086  0.421 0.881     0.00362          0.016 3680 1.000"
"omega[0.5,1]      0.150 0.149 0.003  0.100 0.557     0.00287          0.019 2698 1.000"
"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.    0.050                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   1.640                                          "
""
"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.    0.018              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.574                                          "
""
"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.    0.093                                          "
" Inclusion BF   0.716                                          "
""
"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)   -0.28                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.011             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.042                                                       "
""
"Parameter estimates:"
"               Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau           0.226 0.194 0.039  0.172 0.717     0.00242          0.012 6403 1.002"
"omega[0,0.05] 1.000 0.000 1.000  1.000 1.000          NA             NA   NA 1.000"
"omega[0.05,1] 0.460 0.270 0.056  0.424 0.963     0.00397          0.015 4630 1.001"
"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)   -0.42                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.009             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.906                                                              "
""
"Parameter estimates:"
"                 Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau             0.213 0.183 0.038  0.162 0.676     0.00216          0.012 7167 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] 0.652 0.234 0.169  0.683 0.985     0.00380          0.016 3780 1.000"
"omega[0.1,1]    0.351 0.212 0.050  0.314 0.828     0.00313          0.015 4612 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)   -0.21                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.012             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.112                                                       "
""
"Parameter estimates:"
"               Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau           0.243 0.215 0.041  0.184 0.796     0.00249          0.012 7504 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] 0.454 0.271 0.051  0.418 0.963     0.00394          0.015 4749 1.001"
"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)    0.03                                     tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.015             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.430                                                                "
""
"Parameter estimates:"
"                   Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau               0.220 0.190 0.040  0.167 0.701     0.00220          0.012 7454 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] 0.617 0.246 0.135  0.641 0.984     0.00385          0.016 4067 1.000"
"omega[0.05,1]     0.290 0.206 0.031  0.240 0.788     0.00322          0.016 4103 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)    0.67                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.028             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   2.751                                                              "
""
"Parameter estimates:"
"                 Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau             0.256 0.238 0.040  0.189 0.824     0.00270          0.011 7777 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] 0.634 0.238 0.156  0.662 0.984     0.00380          0.016 3927 1.002"
"omega[0.5,1]    0.216 0.196 0.005  0.155 0.728     0.00365          0.019 2878 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)    0.85                                         tau ~ InvGamma(1, 0.15)       "
" Post. prob.    0.034             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   3.297                                                                       "
""
"Parameter estimates:"
"                   Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau               0.238 0.204 0.039  0.182 0.759     0.00249          0.012 6710 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] 0.724 0.203 0.268  0.765 0.990     0.00353          0.017 3310 1.001"
"omega[0.05,0.5]   0.470 0.220 0.096  0.459 0.898     0.00371          0.017 3509 1.000"
"omega[0.5,1]      0.165 0.160 0.004  0.114 0.590     0.00319          0.020 2509 1.000"
"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   1.245                                          "
""
"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.    0.016              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.515                                          "
""
"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.    0.167                                          "
" Inclusion BF   1.405                                          "
""
"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)   -0.04                               tau ~ Spike(0)          "
" Post. prob.    0.014             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.331                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.405 0.222 -0.015  0.399 0.853     0.00252          0.011 7733 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] 0.533 0.267  0.077  0.529 0.976     0.00398          0.015 4508 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)   -0.29                                   tau ~ Spike(0)             "
" Post. prob.    0.011             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.027                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.377 0.217 -0.027  0.371 0.819     0.00256          0.012 7164 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] 0.680 0.224  0.201  0.715 0.987     0.00366          0.016 3745 1.000"
"omega[0.1,1]    0.407 0.222  0.063  0.383 0.864     0.00339          0.015 4318 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)   -0.23                               tau ~ Spike(0)          "
" Post. prob.    0.011             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.098                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.394 0.236 -0.061  0.393 0.863     0.00274          0.012 7422 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] 0.568 0.259  0.088  0.584 0.977     0.00375          0.014 4771 1.000"
"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)   -0.21                                     tau ~ Spike(0)             "
" Post. prob.    0.012             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.122                                                                "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.353 0.233 -0.087  0.349 0.817     0.00289          0.012 6475 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] 0.670 0.228  0.183  0.708 0.986     0.00366          0.016 3891 1.000"
"omega[0.05,1]     0.389 0.225  0.048  0.361 0.856     0.00339          0.015 4388 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)    0.27                                   tau ~ Spike(0)             "
" Post. prob.    0.019             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.809                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.365 0.253 -0.145  0.370 0.853     0.00298          0.012 7216 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] 0.694 0.220  0.210  0.736 0.989     0.00351          0.016 3945 1.000"
"omega[0.5,1]    0.302 0.232  0.008  0.251 0.825     0.00413          0.018 3147 1.000"
"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)    0.33                                         tau ~ Spike(0)                "
" Post. prob.    0.020             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   1.923                                                                       "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.325 0.248 -0.156  0.326 0.808     0.00291          0.012 7242 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] 0.749 0.194  0.297  0.792 0.991     0.00320          0.016 3683 1.000"
"omega[0.05,0.5]   0.518 0.214  0.123  0.519 0.905     0.00352          0.016 3702 1.000"
"omega[0.5,1]      0.226 0.190  0.005  0.176 0.687     0.00339          0.018 3150 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   0.755                                          "
""
"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.    0.009              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.292                                          "
""
"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.    0.116                                          "
" Inclusion BF   0.921                                          "
""
"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)   -0.46                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.009             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.863                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.382 0.257 -0.107  0.381 0.887     0.00300          0.012 7340 1.000"
"tau           0.189 0.176  0.036  0.136 0.656     0.00219          0.012 6456 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] 0.550 0.262  0.088  0.556 0.975     0.00399          0.015 4310 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)   -0.74                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.007             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.655                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.355 0.247 -0.103  0.348 0.850     0.00286          0.012 7409 1.000"
"tau             0.182 0.158  0.037  0.136 0.591     0.00197          0.012 6460 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] 0.691 0.220  0.212  0.728 0.989     0.00352          0.016 3884 1.000"
"omega[0.1,1]    0.418 0.220  0.070  0.397 0.869     0.00335          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             31                          Parameter prior distributions"
" Prior prob.    0.010                                mu ~ Normal(0, 1)      "
" log(marglik)   -0.58                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.008             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.765                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.355 0.285 -0.215  0.364 0.891     0.00354          0.012 6484 1.000"
"tau           0.206 0.199  0.038  0.147 0.728     0.00251          0.013 6306 1.002"
"omega[0,0.05] 1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.05,1] 0.570 0.262  0.089  0.584 0.981     0.00386          0.015 4605 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)   -0.58                                     tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.008             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.770                                                                "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.296 0.294 -0.299  0.301 0.842     0.00420          0.014 4922 1.001"
"tau               0.206 0.206  0.036  0.146 0.725     0.00286          0.014 5202 1.000"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA 1.001"
"omega[0.025,0.05] 0.669 0.228  0.179  0.704 0.987     0.00379          0.017 3632 1.002"
"omega[0.05,1]     0.383 0.223  0.047  0.354 0.850     0.00351          0.016 4022 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)    0.06                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.015             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.471                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.247 0.364 -0.601  0.284 0.842     0.00546          0.015 4426 1.002"
"tau             0.249 0.266  0.038  0.166 0.954     0.00378          0.014 4936 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] 0.680 0.226  0.192  0.717 0.988     0.00361          0.016 3903 1.000"
"omega[0.5,1]    0.277 0.227  0.007  0.220 0.808     0.00429          0.019 2792 1.001"
"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)    0.10                                         tau ~ InvGamma(1, 0.15)       "
" Post. prob.    0.016             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   1.521                                                                       "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.204 0.365 -0.619  0.236 0.823     0.00573          0.016 4062 1.001"
"tau               0.242 0.244  0.038  0.167 0.851     0.00358          0.015 4649 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] 0.746 0.196  0.286  0.790 0.991     0.00332          0.017 3471 1.000"
"omega[0.05,0.5]   0.511 0.216  0.119  0.511 0.904     0.00374          0.017 3337 1.000"
"omega[0.5,1]      0.197 0.178  0.004  0.144 0.650     0.00341          0.019 2735 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   0.570                                          "
""
"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   0.242                                          "
""
"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)."
