[R-meta] Calculating effect size for subsets of data
kh@nn@ @end|ng |rom hert|e-@choo|@org
Mon Aug 31 13:10:31 CEST 2020
I am conducting a meta-analysis of effect of certain interventions on household energy consumption. In my data set I have a dummy variable for each of the sub-interventions: A,B,C,D such that intersection of A=0 & B=0 & C=0 & D=0 is zero. Each effect size may be associated with multiple interventions though.
I have calculated an aggregate effect size across interventions and then effect size by sub-intervention. But I also want to compare if the effect of the sub-interventions differs from each other. I thought about including the sub-regression dummies as controls in the meta regression:
rma (yi, vi, method = "REML", data = data, mods ~ A*B*C*D)
The problem in interpreting the output of this regression is that there is no base category left for the intercept to denote. Can I perhaps run the model by supressing the intercept? Or what would be the interpretation of the intercept in this case?
Thanks in advance!
10117 Berlin ∙ Germany
khanna using hertie-school.org ∙ www.hertie-school.org<http://www.hertie-school.org/>
[[alternative HTML version deleted]]
More information about the R-sig-meta-analysis