Christina, Page and I like meta-analyses. We are convinced they are a great tool to leverage past research in order to move forward: To gain an overview of the state of a field, to get an idea of research practices, to plan new experiments, and even to get novel theoretical insights.
All three of us are founding members of MetaLab, a website assembling meta-analyses on language acquisition research and offering interactive tools for visualization, power analysis, and experimental planning.
One of our central aims in contributing to creating MetaLab is to motivate others to conduct meta-analyses as well. They can be a great entry for a starting grad student to get an overview over her field AND to get a useful publication out of it. They can be wonderful references for others that are interested in a specific field.
And they are a lot of work.
Because of that, we have proposed to make meta-analyses community-augmented, thus sharing the workload between like-minded researchers and leaving the possibility to let a meta-analysis grow dynamically.
But even when sharing the workload, meta-analyses are still hard. Getting acquainted with the necessary knowledge to run such an analysis requires a lot of reading and learning. That’s why today, we want to share with you our attempt to facilitate this learning process by means of 12 introductory vignettes going through central steps of a meta-analysis. These can be viewed in one go or in little, digestible portions whenever needed. For those who need to or want to read rather than hear the (German-accented) explanatory text, this document has what you need.
We really hope that these can motivate more researchers from the cognitive science community to challenge themselves to conduct a meta-analsysis, collaborate with others on one, or to suggest one to a student.
With that, happy meta-analyzing!
3 thoughts on “How to run a meta-analysis? A video tutorial”
Maybe you’d be interested in the Bayesian approach too:
Code and data:
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Thanks for sharing. This looks like a great extension of standard meta-analyses techniques.
Our current material is meant to cover basics for researchers that are not familiar with the concept of meta-analysis at all – but I am sure readers that are interested in extending their knowledge will find your links very useful!
All our data are also freely available on metalab.stanford.edu and can be fed into Bayesian approaches as wel.