"Call:"
"RoBMA.reg(formula = ~mod_con, data = df_reg, priors = list(mod_con = list(null = prior(\"normal\", "
"    list(0, 0.05)), alt = prior(\"normal\", list(0.3, 0.15)))), "
"    priors_heterogeneity = NULL, priors_bias = list(prior_weightfunction(distribution = \"two.sided\", "
"        parameters = list(alpha = c(1, 1), steps = c(0.05)), "
"        prior_weights = 1/2), prior_PET(distribution = \"Cauchy\", "
"        parameters = list(0, 1), truncation = list(0, Inf), prior_weights = 1/2)), "
"    priors_effect_null = NULL, parallel = TRUE, seed = 1)"
""
"Robust Bayesian meta-analysis"
"Components summary:"
"              Models Prior prob. Post. prob. Inclusion BF"
"Effect           6/6       1.000       1.000          Inf"
"Heterogeneity    0/6       0.000       0.000        0.000"
"Bias             4/6       0.500       0.547        1.205"
""
"Meta-regression components summary:"
"        Models Prior prob. Post. prob. Inclusion BF"
"mod_con    3/6       0.500       1.000 5.371429e+57"
""
"Model-averaged estimates:"
"                Mean Median  0.025 0.975"
"mu            -0.025 -0.006 -0.272 0.046"
"tau            0.000  0.000  0.000 0.000"
"omega[0,0.05]  1.000  1.000  1.000 1.000"
"omega[0.05,1]  0.805  1.000  0.083 1.000"
"PET            0.272  0.000  0.000 2.867"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
"(Estimated publication weights omega correspond to two-sided p-values.)"
""
"Model-averaged meta-regression estimates:"
"            Mean Median  0.025 0.975"
"intercept -0.025 -0.006 -0.272 0.046"
"mod_con    0.924  0.924  0.877 0.973"
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale)."
