ArticleComputational brain & behavior2023
Bayes Factors for Mixed Models: Perspective on Responses.
Article in Computational brain & behavior, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 14 citations in OpenAlex.
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- TrackStudio: An integrated toolkit for markerless tracking.PloS one · 2026Article
- Intrinsic motivation and false feedback reduce the low prevalence effect.Cognitive research: principles and implications · 2025Article
- Multiverse simulation to explore the impact of analytical choices on type I and type II errors in a reaction time study.Behavior research methods · 2025Article
- Real-world estimation taps into basic numeric abilities.Psychonomic bulletin & review · 2025Article
- Temporal distortion for angry faces: Testing visual attention and action preparation accounts.Quarterly journal of experimental psychology (2006) · 2024Article
- Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain.Nature communications · 2024Article
- Associations of cholinergic system integrity with cognitive decline in GBA1 and LRRK2 mutation carriers.NPJ Parkinson's disease · 2024Article
- Article
- Bayes Factors for Mixed Models: Perspective on Responses.Computational brain & behavior · 2023Article
- Revisiting the left ear advantage for phonetic cues to talker identification.The Journal of the Acoustical Society of America · 2022Article
- The effects of induced positive and negative affect on Pavlovian-instrumental interactions.Cognition & emotion · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In van Doorn et al. (2021), we outlined a series of open questions concerning Bayes factors for mixed effects model comparison, with an emphasis on the impact of aggregation, the effect of measurement error, the choice of prior distributions, and the detection of interactions. Seven expert commentaries (partially) addressed these initial questions. Surprisingly perhaps, the experts disagreed (often strongly) on what is best practice-a testament to the intricacy of conducting a mixed effect model comparison. Here, we provide our perspective on these comments and highlight topics that warrant further discussion. In general, we agree with many of the commentaries that in order to take full advantage of Bayesian mixed model comparison, it is important to be aware of the specific assumptions that underlie the to-be-compared models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.