Code to perform the HsMM-MVPA model selection and trial-level GAMM analysis described in Word type and frequency effects on lexical decisions are process-dependent and start early (Krause, van Rij, & Borst; submitted). The code
makes use of the HsMM functions provided by Berberyan et al. (2021) that can be downloaded from here. Additionally, the code requires a copy of the item-level DLP data (Keuleers et al., 2010), which can for example be downloaded here. The vwr R package is required for parts of the trial-level analysis but appears to no longer be on CRAN - the most recent version can still be downloaded from here and then installed locally.
- Clone the repository
- Copy the HsMM functions folder into the repository
- Copy the
dlp-items.Rdataanddlp-stimuli.Rdatafiles into the data folder - Open Matlab and make sure the repository is the working/current directory
- Install eeglab, the parallel computing, and wavelet toolboxes if they are not yet installed
- Run
HSMMMVPA_forward_selection.mat - Open R and make sure the repository is the working/current directory, (optionally) install the dependencies via renv
- Run
trial_level_analyis.Rmd