"Call:"
"RoBMA(r = r, n = n, model_type = \"PSMA\", parallel = TRUE, seed = 1)"
""
"Robust Bayesian meta-analysis"
"Diagnostics overview:"
" Model Prior Effect Prior Heterogeneity                         Prior Bias                         max[error(MCMC)] max[error(MCMC)/SD] min(ESS) max(R-hat)"
"     1     Spike(0)            Spike(0)                                                                          NA                  NA       NA         NA"
"     2     Spike(0)            Spike(0)           omega[two-sided: .05] ~ CumDirichlet(1, 1)                0.00442               0.016     3729      1.001"
"     3     Spike(0)            Spike(0)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00384               0.016     3975      1.001"
"     4     Spike(0)            Spike(0)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00457               0.017     3593      1.001"
"     5     Spike(0)            Spike(0)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00421               0.018     3126      1.000"
"     6     Spike(0)            Spike(0)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00404               0.019     2808      1.000"
"     7     Spike(0)            Spike(0) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00362               0.019     2698      1.000"
"     8     Spike(0)            Spike(0)                             PET ~ Cauchy(0, 1)[0, Inf]              0.00533               0.011     8257      1.001"
"     9     Spike(0)            Spike(0)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.01077               0.011     9037      1.001"
"    10     Spike(0)   InvGamma(1, 0.15)                                                                     0.00301               0.011     8101      1.004"
"    11     Spike(0)   InvGamma(1, 0.15)           omega[two-sided: .05] ~ CumDirichlet(1, 1)                0.00397               0.015     4630      1.002"
"    12     Spike(0)   InvGamma(1, 0.15)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00380               0.016     3780      1.001"
"    13     Spike(0)   InvGamma(1, 0.15)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00394               0.015     4749      1.001"
"    14     Spike(0)   InvGamma(1, 0.15)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00385               0.016     4067      1.001"
"    15     Spike(0)   InvGamma(1, 0.15)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00380               0.019     2878      1.002"
"    16     Spike(0)   InvGamma(1, 0.15) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00371               0.020     2509      1.001"
"    17     Spike(0)   InvGamma(1, 0.15)                             PET ~ Cauchy(0, 1)[0, Inf]              0.00623               0.012     6972      1.000"
"    18     Spike(0)   InvGamma(1, 0.15)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.01282               0.012     7523      1.001"
"    19 Normal(0, 1)            Spike(0)                                                                     0.00218               0.010    10339      1.001"
"    20 Normal(0, 1)            Spike(0)           omega[two-sided: .05] ~ CumDirichlet(1, 1)                0.00398               0.015     4508      1.000"
"    21 Normal(0, 1)            Spike(0)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00366               0.016     3745      1.000"
"    22 Normal(0, 1)            Spike(0)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00375               0.014     4771      1.000"
"    23 Normal(0, 1)            Spike(0)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00366               0.016     3891      1.000"
"    24 Normal(0, 1)            Spike(0)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00413               0.018     3147      1.000"
"    25 Normal(0, 1)            Spike(0) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00352               0.018     3150      1.000"
"    26 Normal(0, 1)            Spike(0)                             PET ~ Cauchy(0, 1)[0, Inf]              0.01348               0.022     1990      1.001"
"    27 Normal(0, 1)            Spike(0)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.01716               0.017     3522      1.000"
"    28 Normal(0, 1)   InvGamma(1, 0.15)                                                                     0.00316               0.012     6929      1.000"
"    29 Normal(0, 1)   InvGamma(1, 0.15)           omega[two-sided: .05] ~ CumDirichlet(1, 1)                0.00399               0.015     4310      1.001"
"    30 Normal(0, 1)   InvGamma(1, 0.15)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00352               0.016     3884      1.000"
"    31 Normal(0, 1)   InvGamma(1, 0.15)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00386               0.015     4605      1.002"
"    32 Normal(0, 1)   InvGamma(1, 0.15)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00420               0.017     3632      1.002"
"    33 Normal(0, 1)   InvGamma(1, 0.15)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00546               0.019     2792      1.002"
"    34 Normal(0, 1)   InvGamma(1, 0.15) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00573               0.019     2735      1.001"
"    35 Normal(0, 1)   InvGamma(1, 0.15)                             PET ~ Cauchy(0, 1)[0, Inf]              0.01383               0.021     2184      1.003"
"    36 Normal(0, 1)   InvGamma(1, 0.15)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.02658               0.020     2480      1.001"
