Simulation-Based Power Analysis in (Generalized) Linear Mixed Models
Author(s) / Creator(s)
Kumle, Levi
Abstract / Description
Vortrag vom 17.05.2023 im Rahmen der Vortragsreihe "Practices and Tools of Open Science (PTOS)"
The statistical power of a research design is closely linked to the reliability and replicability of empirical findings. Accounting for power while planning a study is therefore crucial and often a requirement for submissions in scientific journals. However, this can quickly become highly difficult in practice – especially for more complex, but very popular analysis procedures like linear mixed models (LMMs). In this workshop, we will briefly cover the basics of power analysis, linear mixed models, and why the combination of both requires a simulation-based approach. We will then focus on the R-package mixedpower and how to use it to estimate power in LMMs. The general aim of this workshop will be to help researchers build intuitions about simulation-based power analyses, and to empower them to set up highly powered research designs when they plan to use mixed-effect models to analyse the resultant data. A prerequisite for this workshop is a basic knowledge of R. Although we will briefly cover the basics of LMMs, familiarity with LMMs and the R-package lme4 is strongly recommended.
Persistent Identifier
Date of first publication
2024-04-22
Publisher
ZPID (Leibniz Institute for Psychology)
Citation
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2023_PTOS_2.2_LeviKumle_SimulationBasedPowerAnalyses.webmUnknown - 428.79MBMD5: 8fee7bdfabb3f107e014945d7d89c445
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There are no other versions of this object.
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Author(s) / Creator(s)Kumle, Levi
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PsychArchives acquisition timestamp2024-04-22T10:12:27Z
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Made available on2024-04-22T10:12:27Z
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Date of first publication2024-04-22
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Abstract / DescriptionVortrag vom 17.05.2023 im Rahmen der Vortragsreihe "Practices and Tools of Open Science (PTOS)"de_DE
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Abstract / DescriptionThe statistical power of a research design is closely linked to the reliability and replicability of empirical findings. Accounting for power while planning a study is therefore crucial and often a requirement for submissions in scientific journals. However, this can quickly become highly difficult in practice – especially for more complex, but very popular analysis procedures like linear mixed models (LMMs). In this workshop, we will briefly cover the basics of power analysis, linear mixed models, and why the combination of both requires a simulation-based approach. We will then focus on the R-package mixedpower and how to use it to estimate power in LMMs. The general aim of this workshop will be to help researchers build intuitions about simulation-based power analyses, and to empower them to set up highly powered research designs when they plan to use mixed-effect models to analyse the resultant data. A prerequisite for this workshop is a basic knowledge of R. Although we will briefly cover the basics of LMMs, familiarity with LMMs and the R-package lme4 is strongly recommended.en
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Review statusunknown
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External description on another websitehttps://leibniz-psychology.org/practices-and-tools-of-open-science/simulation-based-power-analysis
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/9887
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.14433
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Language of contenteng
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PublisherZPID (Leibniz Institute for Psychology)
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Is part ofPTOS, 2023, online
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Is related tohttps://leibniz-psychology.org/ptos/
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Is related tohttps://doi.org/10.23668/psycharchives.13172
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Dewey Decimal Classification number(s)150
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TitleSimulation-Based Power Analysis in (Generalized) Linear Mixed Modelsen
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DRO typemovingImage
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DRO typeconferenceObject
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Visible tag(s)ZPID video portal
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Visible tag(s)ZPID Conferences and Workshops