[PDF][PDF] When fixed and random effects mismatch: Implications for model comparisons
J Veríssimo - files.osf.io
Mixed-effects models containing both fixed and random effects have become widely used in
the cognitive sciences, as they are particularly appropriate for the analysis of clustered data …
the cognitive sciences, as they are particularly appropriate for the analysis of clustered data …
[HTML][HTML] When fixed and random effects mismatch: Another case of inflation of evidence in non-maximal models
J Veríssimo - Computational Brain & Behavior, 2023 - Springer
Mixed-effects models that include both fixed and random effects are widely used in the
cognitive sciences because they are particularly suited to the analysis of clustered data …
cognitive sciences because they are particularly suited to the analysis of clustered data …
[HTML][HTML] Benefits of Bayesian model averaging for mixed-effects modeling
DW Heck, F Bockting - Computational Brain & Behavior, 2023 - Springer
Bayes factors allow researchers to test the effects of experimental manipulations in within-
subjects designs using mixed-effects models. van Doorn et al.(2021) showed that such …
subjects designs using mixed-effects models. van Doorn et al.(2021) showed that such …
Model specification in mixed-effects models: a focus on random effects
Mixed-effect models are flexible tools for researchers in a myriad of fields, but that flexibility
comes at the cost of complexity and if users are not careful in how their model is specified …
comes at the cost of complexity and if users are not careful in how their model is specified …
Data aggregation can lead to biased inferences in Bayesian linear mixed models and Bayesian ANOVA: A simulation study
Bayesian linear mixed-effects models and Bayesian ANOVA are increasingly being used in
the cognitive sciences to perform null hypothesis tests, where a null hypothesis that an effect …
the cognitive sciences to perform null hypothesis tests, where a null hypothesis that an effect …
[HTML][HTML] Bayes factor model comparisons across parameter values for mixed models
M Linde, D van Ravenzwaaij - Computational Brain & Behavior, 2023 - Springer
Nested data structures, in which conditions include multiple trials and are fully crossed with
participants, are often analyzed using repeated-measures analysis of variance or mixed …
participants, are often analyzed using repeated-measures analysis of variance or mixed …
[PDF][PDF] Benefits of Bayesian Model Selection and Averaging for Mixed-Effects Modeling
DW Heck, F Bockting - 2021 - files.de-1.osf.io
Bayes factors allow researchers to test the effects of experimental manipulations in within-
subjects designs using mixed-effects models. van Doorn et al.(2021) showed that such …
subjects designs using mixed-effects models. van Doorn et al.(2021) showed that such …
[HTML][HTML] Bayes factors for mixed models: Perspective on responses
In van Doorn et al., 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 …
mixed effects model comparison, with an emphasis on the impact of aggregation, the effect …
[PDF][PDF] Data aggregation can lead to biased inferences in Bayesian linear mixed models and Bayesian ANOVA: A simulation study
Bayesian linear mixed-effects models and Bayesian ANOVA are increasingly being used in
the cognitive sciences to perform null hypothesis tests, where a null hypothesis that an effect …
the cognitive sciences to perform null hypothesis tests, where a null hypothesis that an effect …
The importance of random slopes in mixed models for Bayesian hypothesis testing
K Oberauer - Psychological Science, 2022 - journals.sagepub.com
Mixed models are gaining popularity in psychology. For frequentist mixed models, previous
research showed that excluding random slopes—differences between individuals in the …
research showed that excluding random slopes—differences between individuals in the …