[R-meta] Meta-analyzing gain effects

[Viechtbauer, Wolfgang (NP)]

Dear Zhouhan,

Could you provide a small reproducible toy example illustrating the two different approaches you are contrasting below? I could provide me own interpretation of what it is that you are describing, but it would be a lot easier if you show an example.

Best,
Wolfgang

> -----Original Message-----
> From: R-sig-meta-analysis <r-sig-meta-analysis-bounces using 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 using r-project.org
> Cc: Zhouhan Jin <zjin65 using 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