"Call:"
"RoBMA(d = d, se = d_se, transformation = \"logOR\", 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)   -4.69                            tau ~ Spike(0)"
" Post. prob.    0.068                                          "
" Inclusion BF   0.513                                          "
""
"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)   -3.98                               tau ~ Spike(0)          "
" Post. prob.    0.012             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.109                                                       "
""
"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    NA"
"omega[0.05,1] 0.387 0.272 0.033  0.328 0.953     0.00440          0.016 3806 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)   -4.03                                   tau ~ Spike(0)             "
" Post. prob.    0.011             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.062                                                              "
""
"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    NA"
"omega[0.05,0.1] 0.618 0.247 0.131  0.643 0.983     0.00404          0.016 3723 1.002"
"omega[0.1,1]    0.303 0.208 0.035  0.255 0.796     0.00344          0.017 3664 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)   -4.03                               tau ~ Spike(0)          "
" Post. prob.    0.011             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.058                                                       "
""
"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    NA"
"omega[0.05,1] 0.391 0.270 0.036  0.333 0.950     0.00431          0.016 3941 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)   -3.65                                     tau ~ Spike(0)             "
" Post. prob.    0.016             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.557                                                                "
""
"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    NA"
"omega[0.025,0.05] 0.597 0.259 0.109  0.622 0.982     0.00430          0.017 3625 1.000"
"omega[0.05,1]     0.252 0.201 0.020  0.194 0.756     0.00346          0.017 3383 1.001"
"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)   -3.23                                   tau ~ Spike(0)             "
" Post. prob.    0.024             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   2.381                                                              "
""
"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    NA"
"omega[0.05,0.5] 0.602 0.251 0.125  0.621 0.982     0.00400          0.016 3942 1.000"
"omega[0.5,1]    0.203 0.188 0.005  0.144 0.704     0.00382          0.020 2428 1.001"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
""
"                                                                                            "
" Model              7                                          Parameter prior distributions"
" Prior prob.    0.010                                          mu ~ Spike(0)                "
" log(marglik)   -2.96                                         tau ~ Spike(0)                "
" Post. prob.    0.032             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   3.148                                                                       "
""
"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    NA"
"omega[0.025,0.05] 0.703 0.214 0.234  0.743 0.989     0.00356          0.017 3616 1.000"
"omega[0.05,0.5]   0.432 0.222 0.078  0.412 0.879     0.00377          0.017 3473 1.000"
"omega[0.5,1]      0.150 0.150 0.003  0.101 0.568     0.00303          0.020 2467 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)   -3.56                tau ~ Spike(0)            "
" Post. prob.    0.053                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   1.730                                          "
""
"Parameter estimates:"
"     Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"PET 0.937 0.499 0.103  0.903 2.009     0.00538          0.011 8615 1.000"
"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)   -4.43                tau ~ Spike(0)            "
" Post. prob.    0.022              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.700                                          "
""
"Parameter estimates:"
"       Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"PEESE 2.159 1.140 0.231  2.081 4.579     0.01249          0.011 8339 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)   -4.44                   tau ~ InvGamma(1, 0.15)"
" Post. prob.    0.087                                          "
" Inclusion BF   0.670                                          "
""
"Parameter estimates:"
"     Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau 0.296 0.278 0.046  0.222 0.975     0.00302          0.011 8468 1.007"
"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)   -4.04                               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           0.227 0.190 0.040  0.173 0.707     0.00220          0.012 7425 1.000"
"omega[0,0.05] 1.000 0.000 1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,1] 0.442 0.274 0.044  0.405 0.960     0.00418          0.015 4293 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)   -4.17                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.010             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.919                                                              "
""
"Parameter estimates:"
"                 Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau             0.211 0.185 0.037  0.162 0.675     0.00234          0.013 6217 1.001"
"omega[0,0.05]   1.000 0.000 1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,0.1] 0.640 0.238 0.161  0.668 0.985     0.00385          0.016 3822 1.001"
"omega[0.1,1]    0.338 0.214 0.045  0.298 0.828     0.00326          0.015 4314 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)   -4.01                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.011             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.081                                                       "
""
"Parameter estimates:"
"               Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau           0.245 0.219 0.041  0.186 0.783     0.00249          0.011 7694 1.000"
"omega[0,0.05] 1.000 0.000 1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,1] 0.447 0.271 0.047  0.412 0.959     0.00390          0.014 4831 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)   -3.73                                     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               0.223 0.193 0.039  0.170 0.724     0.00233          0.012 6862 1.001"
"omega[0,0.025]    1.000 0.000 1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.025,0.05] 0.617 0.248 0.129  0.643 0.985     0.00413          0.017 3605 1.001"
"omega[0.05,1]     0.283 0.205 0.029  0.234 0.779     0.00325          0.016 3974 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)   -3.13                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.027             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   2.634                                                              "
""
"Parameter estimates:"
"                 Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau             0.259 0.236 0.042  0.196 0.819     0.00276          0.012 7312 1.000"
"omega[0,0.05]   1.000 0.000 1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,0.5] 0.637 0.239 0.159  0.667 0.984     0.00395          0.017 3661 1.000"
"omega[0.5,1]    0.214 0.194 0.005  0.155 0.717     0.00337          0.017 3298 1.000"
"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)   -2.94                                         tau ~ InvGamma(1, 0.15)       "
" Post. prob.    0.033             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   3.218                                                                       "
""
"Parameter estimates:"
"                   Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau               0.239 0.208 0.040  0.183 0.757     0.00241          0.012 7433 1.000"
"omega[0,0.025]    1.000 0.000 1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.025,0.05] 0.718 0.207 0.252  0.756 0.990     0.00346          0.017 3583 1.000"
"omega[0.05,0.5]   0.461 0.219 0.092  0.448 0.890     0.00362          0.016 3676 1.000"
"omega[0.5,1]      0.158 0.152 0.004  0.109 0.558     0.00280          0.018 2933 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)   -3.83                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.041                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   1.309                                          "
""
"Parameter estimates:"
"     Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau 0.215 0.228 0.036  0.153 0.726     0.00234          0.010 9504 1.000"
"PET 0.885 0.535 0.068  0.819 2.053     0.00648          0.012 6804 1.001"
"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)   -4.57                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.019              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.611                                          "
""
"Parameter estimates:"
"       Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"tau   0.235 0.244 0.037  0.167 0.812     0.00261          0.011 8772 1.000"
"PEESE 2.092 1.225 0.179  1.979 4.730     0.01332          0.011 8457 1.000"
"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)   -3.79                        tau ~ Spike(0)    "
" Post. prob.    0.168                                          "
" Inclusion BF   1.411                                          "
""
"Parameter estimates:"
"    Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu 0.474 0.215 0.048  0.475 0.891     0.00221          0.010 9468 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)   -3.76                               tau ~ Spike(0)          "
" Post. prob.    0.014             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.396                                                       "
""
"Parameter estimates:"
"               Mean    SD   lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.395 0.211 0.000  0.388 0.824     0.00245          0.012 7451 1.000"
"omega[0,0.05] 1.000 0.000 1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,1] 0.518 0.270 0.068  0.515 0.973     0.00404          0.015 4479 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)   -4.00                                   tau ~ Spike(0)             "
" Post. prob.    0.011             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.086                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.372 0.209 -0.013  0.364 0.806     0.00238          0.011 7688 1.001"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,0.1] 0.672 0.228  0.187  0.709 0.988     0.00370          0.016 3799 1.001"
"omega[0.1,1]    0.398 0.222  0.059  0.370 0.858     0.00332          0.015 4493 1.001"
"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)   -3.98                               tau ~ Spike(0)          "
" Post. prob.    0.012             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   1.117                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.394 0.220 -0.031  0.392 0.825     0.00262          0.012 7045 1.000"
"omega[0,0.05] 1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,1] 0.564 0.262  0.086  0.579 0.977     0.00369          0.014 5027 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)   -3.93                                     tau ~ Spike(0)             "
" Post. prob.    0.012             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.167                                                                "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.348 0.223 -0.078  0.345 0.798     0.00279          0.013 6384 1.001"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.025,0.05] 0.671 0.230  0.178  0.709 0.988     0.00375          0.016 3773 1.000"
"omega[0.05,1]     0.383 0.226  0.046  0.351 0.857     0.00359          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             24                                 Parameter prior distributions"
" Prior prob.    0.010                                    mu ~ Normal(0, 1)         "
" log(marglik)   -3.51                                   tau ~ Spike(0)             "
" Post. prob.    0.019             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.791                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.363 0.242 -0.118  0.366 0.828     0.00277          0.011 7654 1.000"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,0.5] 0.685 0.221  0.208  0.724 0.988     0.00346          0.016 4076 1.001"
"omega[0.5,1]    0.301 0.228  0.009  0.254 0.812     0.00376          0.016 3678 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)   -3.44                                         tau ~ Spike(0)                "
" Post. prob.    0.020             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   1.925                                                                       "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.322 0.237 -0.150  0.326 0.779     0.00281          0.012 7110 1.000"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.025,0.05] 0.746 0.195  0.291  0.791 0.992     0.00322          0.017 3668 1.001"
"omega[0.05,0.5]   0.505 0.217  0.114  0.504 0.907     0.00352          0.016 3778 1.001"
"omega[0.5,1]      0.219 0.185  0.006  0.170 0.669     0.00328          0.018 3177 1.004"
"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)   -4.31                tau ~ Spike(0)            "
" Post. prob.    0.025                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   0.791                                          "
""
"Parameter estimates:"
"     Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  0.207 0.326 -0.547  0.242 0.758     0.00759          0.023 1844 1.000"
"PET 0.755 0.686  0.026  0.556 2.619     0.01728          0.025 1575 1.002"
"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)   -5.15                tau ~ Spike(0)            "
" Post. prob.    0.011              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.338                                          "
""
"Parameter estimates:"
"       Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu    0.269 0.271 -0.307  0.282 0.767     0.00452          0.017 3601 1.001"
"PEESE 1.487 1.205  0.050  1.199 4.463     0.02210          0.018 2975 1.001"
"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)   -4.17                   tau ~ InvGamma(1, 0.15)"
" Post. prob.    0.115                                          "
" Inclusion BF   0.913                                          "
""
"Parameter estimates:"
"     Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  0.452 0.267 -0.077  0.456 0.974     0.00297          0.011 8117 1.002"
"tau 0.205 0.206  0.036  0.142 0.734     0.00248          0.012 6884 1.001"
"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)   -4.20                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.009             omega[two-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.892                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.373 0.249 -0.101  0.369 0.861     0.00283          0.011 7764 1.000"
"tau           0.189 0.168  0.036  0.139 0.636     0.00198          0.012 7242 1.000"
"omega[0,0.05] 1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,1] 0.533 0.265  0.078  0.531 0.974     0.00401          0.015 4380 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)   -4.47                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.007             omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.677                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.350 0.241 -0.098  0.343 0.833     0.00271          0.011 7911 1.001"
"tau             0.181 0.161  0.037  0.133 0.592     0.00192          0.012 7061 1.001"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,0.1] 0.679 0.226  0.199  0.715 0.989     0.00367          0.016 3791 1.001"
"omega[0.1,1]    0.406 0.218  0.068  0.381 0.856     0.00318          0.015 4715 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)   -4.35                               tau ~ InvGamma(1, 0.15) "
" Post. prob.    0.008             omega[one-sided: .05] ~ CumDirichlet(1, 1)"
" Inclusion BF   0.766                                                       "
""
"Parameter estimates:"
"               Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu            0.352 0.276 -0.216  0.360 0.866     0.00340          0.012 6567 1.000"
"tau           0.207 0.208  0.038  0.147 0.727     0.00242          0.012 7362 1.000"
"omega[0,0.05] 1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,1] 0.565 0.261  0.087  0.581 0.977     0.00379          0.015 4734 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)   -4.32                                     tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.008             omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   0.786                                                                "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.305 0.282 -0.262  0.312 0.822     0.00373          0.013 5714 1.003"
"tau               0.199 0.193  0.036  0.143 0.693     0.00255          0.013 5692 1.001"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.025,0.05] 0.674 0.227  0.188  0.710 0.987     0.00347          0.015 4270 1.001"
"omega[0.05,1]     0.390 0.225  0.045  0.364 0.857     0.00333          0.015 4565 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)   -3.73                                   tau ~ InvGamma(1, 0.15)    "
" Post. prob.    0.015             omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)"
" Inclusion BF   1.431                                                              "
""
"Parameter estimates:"
"                 Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu              0.248 0.356 -0.584  0.283 0.843     0.00530          0.015 4515 1.001"
"tau             0.248 0.254  0.039  0.169 0.901     0.00364          0.014 4892 1.000"
"omega[0,0.05]   1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.05,0.5] 0.680 0.224  0.197  0.717 0.987     0.00345          0.015 4232 1.001"
"omega[0.5,1]    0.270 0.227  0.006  0.208 0.804     0.00403          0.018 3174 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)   -3.69                                         tau ~ InvGamma(1, 0.15)       "
" Post. prob.    0.016             omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)"
" Inclusion BF   1.499                                                                       "
""
"Parameter estimates:"
"                   Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu                0.215 0.354 -0.620  0.248 0.814     0.00563          0.016 3956 1.004"
"tau               0.239 0.244  0.037  0.163 0.874     0.00357          0.015 4691 1.002"
"omega[0,0.025]    1.000 0.000  1.000  1.000 1.000          NA             NA   NA    NA"
"omega[0.025,0.05] 0.743 0.198  0.282  0.787 0.991     0.00340          0.017 3388 1.000"
"omega[0.05,0.5]   0.509 0.217  0.117  0.507 0.904     0.00368          0.017 3488 1.001"
"omega[0.5,1]      0.205 0.184  0.004  0.151 0.668     0.00348          0.019 2807 1.002"
"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)   -4.61                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.019                PET ~ Cauchy(0, 1)[0, Inf]"
" Inclusion BF   0.587                                          "
""
"Parameter estimates:"
"     Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu  0.168 0.375 -0.681  0.208 0.801     0.00800          0.021 2197 1.000"
"tau 0.222 0.225  0.038  0.154 0.810     0.00269          0.012 6985 1.001"
"PET 0.790 0.725  0.025  0.577 2.710     0.01689          0.023 1844 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)   -5.35                tau ~ InvGamma(1, 0.15)   "
" Post. prob.    0.009              PEESE ~ Cauchy(0, 5)[0, Inf]"
" Inclusion BF   0.277                                          "
""
"Parameter estimates:"
"       Mean    SD    lCI Median   uCI error(MCMC) error(MCMC)/SD  ESS R-hat"
"mu    0.189 0.354 -0.591  0.220 0.804     0.00603          0.017 3447 1.001"
"tau   0.252 0.281  0.039  0.168 0.953     0.00409          0.015 4721 1.002"
"PEESE 1.764 1.492  0.061  1.404 5.499     0.02901          0.019 2643 1.000"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
