"Call:"
"RoBMA(d = d, se = d_se, transformation = \"logOR\", 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)                0.00440               0.016     3806      1.001"
"     3     Spike(0)            Spike(0)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00404               0.017     3664      1.002"
"     4     Spike(0)            Spike(0)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00431               0.016     3941      1.000"
"     5     Spike(0)            Spike(0)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00430               0.017     3383      1.001"
"     6     Spike(0)            Spike(0)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00400               0.020     2428      1.001"
"     7     Spike(0)            Spike(0) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00377               0.020     2467      1.001"
"     8     Spike(0)            Spike(0)                             PET ~ Cauchy(0, 1)[0, Inf]              0.00538               0.011     8615      1.000"
"     9     Spike(0)            Spike(0)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.01249               0.011     8339      1.001"
"    10     Spike(0)   InvGamma(1, 0.15)                                                                     0.00302               0.011     8468      1.007"
"    11     Spike(0)   InvGamma(1, 0.15)           omega[two-sided: .05] ~ CumDirichlet(1, 1)                0.00418               0.015     4293      1.001"
"    12     Spike(0)   InvGamma(1, 0.15)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00385               0.016     3822      1.001"
"    13     Spike(0)   InvGamma(1, 0.15)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00390               0.014     4831      1.000"
"    14     Spike(0)   InvGamma(1, 0.15)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00413               0.017     3605      1.001"
"    15     Spike(0)   InvGamma(1, 0.15)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00395               0.017     3298      1.000"
"    16     Spike(0)   InvGamma(1, 0.15) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00362               0.018     2933      1.000"
"    17     Spike(0)   InvGamma(1, 0.15)                             PET ~ Cauchy(0, 1)[0, Inf]              0.00648               0.012     6804      1.001"
"    18     Spike(0)   InvGamma(1, 0.15)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.01332               0.011     8457      1.000"
"    19 Normal(0, 1)            Spike(0)                                                                     0.00221               0.010     9468      1.000"
"    20 Normal(0, 1)            Spike(0)           omega[two-sided: .05] ~ CumDirichlet(1, 1)                0.00404               0.015     4479      1.000"
"    21 Normal(0, 1)            Spike(0)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00370               0.016     3799      1.001"
"    22 Normal(0, 1)            Spike(0)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00369               0.014     5027      1.001"
"    23 Normal(0, 1)            Spike(0)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00375               0.016     3773      1.001"
"    24 Normal(0, 1)            Spike(0)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00376               0.016     3678      1.001"
"    25 Normal(0, 1)            Spike(0) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00352               0.018     3177      1.004"
"    26 Normal(0, 1)            Spike(0)                             PET ~ Cauchy(0, 1)[0, Inf]              0.01728               0.025     1575      1.002"
"    27 Normal(0, 1)            Spike(0)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.02210               0.018     2975      1.001"
"    28 Normal(0, 1)   InvGamma(1, 0.15)                                                                     0.00297               0.012     6884      1.002"
"    29 Normal(0, 1)   InvGamma(1, 0.15)           omega[two-sided: .05] ~ CumDirichlet(1, 1)                0.00401               0.015     4380      1.000"
"    30 Normal(0, 1)   InvGamma(1, 0.15)       omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)             0.00367               0.016     3791      1.001"
"    31 Normal(0, 1)   InvGamma(1, 0.15)           omega[one-sided: .05] ~ CumDirichlet(1, 1)                0.00379               0.015     4734      1.000"
"    32 Normal(0, 1)   InvGamma(1, 0.15)     omega[one-sided: .05, .025] ~ CumDirichlet(1, 1, 1)             0.00373               0.015     4270      1.003"
"    33 Normal(0, 1)   InvGamma(1, 0.15)       omega[one-sided: .5, .05] ~ CumDirichlet(1, 1, 1)             0.00530               0.018     3174      1.001"
"    34 Normal(0, 1)   InvGamma(1, 0.15) omega[one-sided: .5, .05, .025] ~ CumDirichlet(1, 1, 1, 1)          0.00563               0.019     2807      1.004"
"    35 Normal(0, 1)   InvGamma(1, 0.15)                             PET ~ Cauchy(0, 1)[0, Inf]              0.01689               0.023     1844      1.001"
"    36 Normal(0, 1)   InvGamma(1, 0.15)                           PEESE ~ Cauchy(0, 5)[0, Inf]              0.02901               0.019     2643      1.002"
