I'm new in this blog and my knowledge in R is very weak. However, I was trying to set the intercept at 1 in the following rma.mv ('metafor' package) function:
rma.mv(S_ratio, Variance, data=dat_S_ratio, mods= ~ N_Total_e, random= ~1|Primary_Study)
Basically I want to force the function to pass from the point (0,1). I assume thus, that S_ratio value is 1 when N_Total_e is 0. There are many examples on how to do that with fixed effect models (e.g. 'lm'), while I found no examples for functions fitted with random effect models (e.g. 'rma.mv' or 'lme').
Do you know if that is possible also in models with more that 1 moderator variables? For example:
rma.mv(S_ratio, Variance, data=dat_S_ratio, mods= ~ N_Total_e + MAP_e + MAT_e, random= ~1|Primary_Study)