"Call:"
"RoBMA(d = d, se = d_se, model_type = \"2w\", parallel = TRUE, seed = 1)"
""
"Robust Bayesian meta-analysis"
"Models overview:"
" Model Prior Effect Prior Heterogeneity                     Prior Bias                     Prior prob. log(marglik) Post. prob. Inclusion BF"
"     1     Spike(0)            Spike(0)                                                          0.125        -0.83       0.082        0.625"
"     2     Spike(0)            Spike(0)      omega[two-sided: .05] ~ CumDirichlet(1, 1)          0.062        -0.30       0.070        1.127"
"     3     Spike(0)            Spike(0)  omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)       0.062        -0.38       0.064        1.034"
"     4     Spike(0)   InvGamma(1, 0.15)                                                          0.125        -0.62       0.102        0.794"
"     5     Spike(0)   InvGamma(1, 0.15)      omega[two-sided: .05] ~ CumDirichlet(1, 1)          0.062        -0.35       0.067        1.070"
"     6     Spike(0)   InvGamma(1, 0.15)  omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)       0.062        -0.51       0.057        0.901"
"     7 Normal(0, 1)            Spike(0)                                                          0.125        -0.03       0.184        1.574"
"     8 Normal(0, 1)            Spike(0)      omega[two-sided: .05] ~ CumDirichlet(1, 1)          0.062        -0.11       0.085        1.393"
"     9 Normal(0, 1)            Spike(0)  omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)       0.062        -0.38       0.065        1.037"
"    10 Normal(0, 1)   InvGamma(1, 0.15)                                                          0.125        -0.39       0.128        1.024"
"    11 Normal(0, 1)   InvGamma(1, 0.15)      omega[two-sided: .05] ~ CumDirichlet(1, 1)          0.062        -0.52       0.056        0.892"
"    12 Normal(0, 1)   InvGamma(1, 0.15)  omega[two-sided: .1, .05] ~ CumDirichlet(1, 1, 1)       0.062        -0.82       0.042        0.651"
