Dear R meta Community,
I have a general question. When meta-analyzing quasi-experimental longitudinal studies, I wonder which approach I should take to estimate the gains:
1- Meta-analyze effects (e.g., SMDs) at each time point and then after modeling, run appropriate hypotheses to estimate treatments' gains meta-analytically?
OR
2- Compute gain effects (e.g., SMCCs in escalc) in the dataset, and meta-analyze them by a model to estimate the treatments' gains directly?
Thank you so much and I look forward to hearing your thoughts!
Best wishes,
Zhouhan