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  Toward cumulative cognitive science: a comparison of meta-analysis, mega-analysis, and hybrid approaches

Koile, E., & Cristia, A.(2021). Toward cumulative cognitive science: a comparison of meta-analysis, mega-analysis, and hybrid approaches (shh3034). doi:10.1162/opmi_a_00048.

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 Creators:
Koile, Ezequiel1, Author              
Cristia, Alejandrina, Author
Affiliations:
1Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2074311              

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Free keywords: cumulative science, open science, meta-analyses, mega-analyses, data simulation, fixed effects, random effects
 Abstract: There is increasing interest in cumulative approaches to science, in which instead of analyzing the results of individual papers separately, we integrate information qualitatively or quantitatively. One such approach is meta-analysis, which has over 50 years of literature supporting its usefulness, and is becoming more common in cognitive science. However, changes in technical possibilities by the widespread use of Python and R make it easier to fit more complex models, and even simulate missing data. Here we recommend the use of mega-analyses (based on the aggregation of data sets collected by independent researchers) and hybrid meta- mega-analytic approaches, for cases where raw data is available for some studies. We illustrate the three approaches using a rich test-retest data set of infants’ speech processing as well as synthetic data. We discuss advantages and disadvantages of the three approaches from the viewpoint of a cognitive scientists contemplating their use, and limitations of this article, to be addressed in future work.

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Language(s): eng - English
 Dates: 2021-10-01
 Publication Status: Published online
 Pages: 20
 Publishing info: -
 Table of Contents: Introduction
- Study Case: Reliability of Infant Speech Perception Measures
- Alternatives to Meta-analyses: Mega-analyses, IPD Meta-analyses, and Hybrid Approaches
The present study
- A Brief Primer on Test-Retest Infant Speech Perception
- Modeling
Experiment 1: Natural data
Experiment 2: Synthetic data
General discussion
- Potential Limitations
Conclusion
 Rev. Type: -
 Identifiers: DOI: 10.1162/opmi_a_00048
Other: shh3034
 Degree: -

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Title: Open mind : discoveries in cognitive science
  Other : Open mind
Source Genre: Journal
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Publ. Info: Cambridge, Mass. : The MIT Press
Pages: - Volume / Issue: - Sequence Number: 00048 Start / End Page: 1 - 20 Identifier: ISSN: 2470-2986
CoNE: https://pure.mpg.de/cone/journals/resource/2470-2986