Completely edited: If a meta-analysis include many studies that reported multiple effect sizes within each study, multi-level meta-analysis is one way to account for this dependency in effect sizes. However, there seems to be two approaches: one that utilize the traditional multilevel models and another that utilize multilevel structural equation modeling (uses metaSEM package; Cheung, 2014)
In regular multi-level modeling, the three levels are:
Level 1- effect size
Level 2- within-study variation
Level 3- between-study variation
However, it's unclear to me what the three levels are for the multilevel SEM approach. Is it the same? Some papers that used metaSEM and cited Cheung 2014 (e.g., Lebuda et al., 2016) describes the three levels as:
Level 1- study participants
Level 2- effect sizes (within-study variation)
Level 3- study (between-study variation)
My questions are:
1. Did Lebuda et al., 2016 have it right that those are indeed the three levels?
2. If so, how is it possible to have level 1 as study participants given that in meta-analysis you typically don't have data at the participant level?
3. What's the added advantage to using multilevel SEM vs. just multilevel approach?
Weisz, J. R., Kuppens, S., Ng, M. Y., Eckshtain, D., Ugueto, A. M., Vaughn-Coaxum, R., ... & Weersing, V. R. (2017). What five decades of research tells us about the effects of youth psychological therapy: A multilevel meta-analysis and implications for science and practice. American Psychologist, 72(2), 79.
Paper that used metaSEM to do multilevel SEM meta-analysis and describes the three levels:
Lebuda, I., Zabelina, D. L., & Karwowski, M. (2016). Mind full of ideas: A meta-analysis of the mindfulness–creativity link. Personality and Individual Differences, 93, 22-26.