The DOI matches its Crossref record; 47 of the 49 references it cites were found in a registry or an index.
Examples of mixed-effects modeling with crossed random effects and with binomial data
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“As a result, there is a growing body of literature that argues it is more appropriate to use generalized linear mixed-effects probit/logit models to analyze these types of accuracy data (Dixon, 2008; Jaeger, 2008; Quené and van den Bergh, 2008; Song et al., 2017).”
From Cognitive Mapping Without Vision: Comparing Wayfinding Performance After Learning From Digital Touchscreen-Based Multimodal Maps vs. Embossed Tactile Overlays (2020) · cites this paper as Quené and van den Bergh, 2008
Citations
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Random effects structure for confirmatory hypothesis testing: Keep it maximal
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Metadata
- Authors
- Quené, H., & van den Bergh, H.
- Affiliations
- Utrecht University (NL)
- Corresponding author
- Quené, Hugo
- Venue
- Journal of Memory and Language
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 59
- Issue
- 4
- Pages
- 413-425
- ISSN
- 0749-596X (ISSN-L)
- OpenAlex
- W1988055263
- Cited by
- 534
- References
- 49
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 17 · 2023: 19 · 2022: 17 · 2021: 44 · 2020: 38 · 2019: 44 · 2018: 44 · 2017: 41 · 2016: 23 · 2015: 28 · 2014: 48 · 2013: 46 · 2012: 33
- FWCI
- 20.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Memory and Language (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Universiteit Utrecht
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Keywords
- mixed models, crossed random effects, binomial data, generalized linear mixed models, repeated measures ANOVA, type I error
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