I'm currently conducting a meta-regression for my moderators from a meta-analysis my team recently conducted. In calculating the fixed effects meta-regressions, my objective is to identify how much heterogeneity is accounted for when the moderators are considered in the model. To do this, I used the
rma() function from the
metafor package in R:
Reg1 <- rma(yi = LogOdds, sei = SE, data = data, method = 'FE', mods = ~ mod1 + mod2)
The output provides out $I^2$ and $H^2$ values as well as the significance of our moderators, however, it does not provide an $R^2$ value for the amount of heterogeneity accounted for.
I did notice, however, that running an random effects meta regression dos provide the $R^2$.
My questions are: Does a meta-regression have to be random effects in order to garner the amount of heterogeneity accounted for? If I ran a fixed effects meta-analysis, must I also run a fixed effects meta-regression? And if not, how can I estimate the amount of heterogeneity accounted for in a fixed effects meta-regression?