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the claim
Open science workflows enable reproducible meta-analyses in psychological research.
the verdict
SUPPORTED
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the weight of evidence
1 source for · 0 against

Peer-reviewed literature demonstrates that open science frameworks and platforms enable transparent and reproducible meta-analyses within developmental psychology.

Evidence for · 1
2021 · cited by 0
Meta-analyses provide researchers with an overview of the body of evidence in a topic, with quantified estimates of effect sizes and the role of moderators, and weighting studies according to their precision. We provide a guide for conducting a transparent and reproducible meta-analysis in the field of developmental psychology within the framework of the MetaLab platform, in 10 steps: 1) Choose a topic for your meta-analysis, 2) Formulate your research question and specify inclusion criteria, 3) Preregister and document all stages of your meta-analysis, 4) Conduct the literature search, 5) Collect and screen records, 6) Extract data from eligible studies, 7) Read the data into analysis software and compute effect sizes, 8) Visualize your data, 9) Create meta-analytic models to assess the strength of the effect and investigate possible moderators, 10) Write up and promote your meta-analysis. Meta-analyses can inform future studies, through power calculations, by identifying robust methods and exposing research gaps. By adding a new meta-analysis to MetaLab, datasets across multiple topics of developmental psychology can be synthesized, and the dataset can be maintained as a living, community-augmented meta-analysis to which researchers add new data, allowing for a cumulative approach to evidence synthesis.
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The analysis

rails:sufficiency:supported:single_source:for=1+0p:against=0+0p | v55:sufficiency

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  1. Ten easy steps to conducting transparent, reproducible meta-analyses for infant researcherspeer-reviewedno side taken
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