26 Oct 2022 TI Methods Speaker Series: Exploring heterogeneity in meta-analysis
This live webinar has already taken place. Scroll down to view the video recording.
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When analyzing a heterogeneous body of literature, between-studies differences can be coded as moderators and accounted for using meta-regression. When the number of potential moderators is high relative to the number of studies, however, statistical power to detect relevant moderators may be low. This presentation introduced machine learning-based methods to perform moderator selection in meta-analysis, specifically, a random forests-based approach (MetaForest) and Bayesian regularized meta-regression (BRMA). These approaches identify relevant moderators from a selection of potential candidates.
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WHEN: Wednesday, October 26th, 2022 from 12:00 to 1:00 PM PDT [convert to your time zone]
WHERE: Offered online using the Zoom platform.
TITLE: Exploring heterogeneity in meta-analysis
SPEAKER: Dr. Caspar J. van Lissa, Associate Professor, Tilburg University, the Netherlands
About the Speaker: Dr. Caspar J. Van Lissa is associate professor of social data science at Tilburg University, the Netherlands. He serves as chair of the local Open Science Community, and is associate editor for Research Synthesis Methods and statistical consulting editor for Child Development. His primary research line uses machine learning for rigorous exploration to complement blind spots in theory. His secondary research line centers on machine learning-based evidence synthesis: Summarizing existing knowledge, e.g. through systematic reviews and meta-analysis.
About the TI Methods Speaker Series: The TI Methods Speaker Series are offered free of charge and everyone is welcome. The event is held at noon on the last Wednesday of each month via videoconference. The presentations are recorded and the video recordings are posted online. Click here to view the scheduled topics for 2022 and click here to view a list of TI Methods Speaker Series talks offered in 2021.
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