Introduction Comparing the four BF methods Evidence for null hypothesis: brms vs. ttestBF() How much more conservative is the bmrs approach? Directed vs. non-directed hypothesis Conclusion Introduction In this post, I’d like to examine how different ways to calcualte Bayes factors (BF) compare with each other for a simple model.
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Aim of this document The aim of this document is to accompany the design analysis for noveltyVR (see here) and to shed light on the deliberations concerning the planned analysis.
The planned design is a 2 x 2 x 2 design with one between and two within subject factors. There will be a novelty and a control group (Factor N) and we will examine recollection/familiarity (Factor M) for weakly/strongly learned words (Factor E).
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Preface Note: This is an old post from my early PhD time that I slightly edited but share again because it would be interesting to one or two people.
This work documents my attempt to understand the model structure of mixed linear models or multilevel models. I adapted a formula that I found on Wikipedia and work myself through the different models and test whether I am able to retrieve the different parameters with lmerTest.
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Introduction In order to be able to present object at locations with a range of expectancy values, which is crucial to show that this has U-shaped relationship, I asked six member of my research group. to rate all combinations of objects and location that exist in the virtual environment for the schemaVR task.
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