Prelude Sources that I found useful General libraries Simple linear regression Multiple linear regression Special cases One sample t-test Two sample t-test Paired t-test Two-way ANOVA Does the contrast weighting matter for the test-statistics? Covariance matrix of the residuals A example design matrix for fMRI Multiple testing problem Calculate FWE FWE correction Random field theory Permutation tests FDR Conclusion Glossary Prelude I was revisiting some of the basics surrounding fMRI especially the GLM and contrasts.
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The problem While analysing the data from our U-shape experiments (see pre-registration for context: https://osf.io/kcr2q), we ran into a peculiar problem. As expected, we did find that memory performance can be described as a U-shape function of how expected a certain object is in certain location. However, we also predicted that the memory advantage for highly incongruent item/locations pairings as well as for highly congruent pairings are driven by different processes.
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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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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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