Random-effects Model
# fit a random-effects model
res <- rma(yi, vi, data=dat)
res
##
## Random-Effects Model (k = 51; tau^2 estimator: REML)
##
## tau^2 (estimated amount of total heterogeneity): 0.0179 (SE = 0.0050)
## tau (square root of estimated tau^2 value): 0.1338
## I^2 (total heterogeneity / total variability): 78.33%
## H^2 (total variability / sampling variability): 4.61
##
## Test for Heterogeneity:
## Q(df = 50) = 188.5421, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## 0.0978 0.0224 4.3635 <.0001 0.0539 0.1417 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1