read data
dataset ← read_xlsx(“Tonal_Hierarchy_2022_01_19.xlsx”)
Tonal_Hierarchy_raw<- data.frame(dataset)
calculate z-transformed effect sizes
Tonal_Hierarchy_ztrans ← escalc(measure= “ZCOR”, ri = r, ni = N, data = Tonal_Hierarchy_raw)
set priors
priors ← c(prior(normal(0, 1), class = Intercept),
prior(cauchy (0, 0.5), class = sd))
fit two-level-model
fit_sbi_2 ← brm(yi |se (sqrt(vi)) ~ 1 + (1 | Study_ID) + (1 |ES_ID),
data = Tonal_Hierarchy_ztrans,
prior = priors,
seed = 20121220,
control = list(max_treedepth = 15,
adapt_delta = .999))
summary(fit_sbi_2)
Hello everyone,
I conducted a meta-analysis with Fisher’s z-transformed correlation coefficients. How can I back-transform the brm-model output into correlation coefficients r for reporting results and presentation of a forest-plot?
Thank you so much!
Kind regards, Hanna