"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)"
""
"Estimates:"
"    intercept       mod_con           tau omega[0,0.05] omega[0.05,1]           PET "
"  -0.02541555    0.92412307    0.00000000    1.00000000    0.80513692    0.27151767 "
