Meta-analytic structural equation modeling (MASEM) refers to fitting structural equation models (SEMs) (such as path models or factor models) to meta-analytic data. Currently, fitting MASEMs may be challenging for researchers that are not accustomed to working with R software and packages. In solution, there is webMASEM; a web application for MASEM. This app implements the one-stage MASEM approach, and allows users to apply MASEM in a user-friendly way.
Developed by Dr. Victor Zitian Chen ([email protected]) and Crystal Wen Zheng ([email protected]) at the University of North Carolina at Charlotte, EMIE2.0 is an R shiny tool built for curating and visualizing relationship knowledge data, with a preloaded data of meta-analytic findings of drivers for organizational performance outcomes.
Meta-analyses are predicated on the assumption of independence of primary effect sizes, which might be routinely violated in the organizational sciences. In HubMeta, we get around this by routinely creating composite scores to ensure independence. As an alternative, meta-analysis could be cast as a multilevel, variance known (Vknown) model to account for such dependency in primary studies’ effect sizes.
Meta-Sen is a cloud-based, open access software that allows users to upload a meta-analytic dataset and provides as output all essential meta-analytic results and sensitivity analysis results.
Field, J. G., Bosco, F. A., & Kepes, S. (2020). How robust is our cumulative knowledge on turnover? Journal of Business and Psychology, 1-17.
Treating all moderators as independent, it helps determine the range of results your meta-analytic matrix could generate.
Yu, J. J., Downes, P. E., Carter, K. M., & O’Boyle, E. (2018). The heterogeneity problem in meta‐analytic structural equation modeling (MASEM) revisited: A reply to Cheung. Journal of Applied Psychology, 103(7), 804– 811.
Allowing the non-specialist user to carry out a popular complex analysis method, NMA, in an interactive environment within an internet browser window
Owen, R. K., Bradbury, N., Xin, Y., Cooper, N., & Sutton, A. (2019). MetaInsight: An interactive web‐based tool for analyzing, interrogating, and visualizing network meta‐analyses using R‐shiny and netmeta. Research Synthesis Methods, 10(4), 569-581.
You can run this with a matrix, so makes a nice addition to any MASEM analysis.
Open Science Foundation links for registering your meta-analysis, including a generic registration form
A curation of other meta-analytic related resources: