-----Original Message-----
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> On Behalf
Of Zhouhan Jin via R-sig-meta-analysis
Sent: Monday, March 11, 2024 15:27
To: r-sig-meta-analysis at r-project.org
Cc: Zhouhan Jin <zjin65 at uwo.ca>
Subject: [R-meta] Meta-analyzing gain effects
Dear R meta Community,
(reposting this as I think my first message fell through the cracks)
When meta-analyzing quasi-experimental longitudinal studies, I wonder which
approach I should take to estimate the gains:
1- Meta-analyze the effects (e.g., SMDs) at each time point and then after
modeling, run appropriate hypotheses to estimate treatments' gains meta-
analytically?
OR
2- Compute the gain effects (e.g., SMCCs in escalc) in the dataset, and meta-
analyze them by a model to estimate the treatments' gains directly?
PS. I personally prefer the first approach as it doesn't directly require the
pre-post correlations.
Best wishes,
Zhouhan