This GitHub page contains linear mixed effects model (LME) resources and scripts from Heise, Mon, and Bowman (2022):
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LMEIntroResources: List of recommended introductory textbooks, papers, and websites for linear mixed effects models.
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LMETutorialScripts: Tutorial pipeline for processing continuous EEG data files and calculating trial-level ERP waveforms in MATLAB. Mean amplitude values are then exported into R and analyzed with LME models. This pipeline was described in Appendix D of Heise et al. (2022).
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SimulationScripts: Pipeline for simulating developmental ERP data with realistic data missingness patterns. Script parameters (e.g., age-related mean amplitude difference, neural noise characteristics) and supplemental analyses were reported in Section 3 and Appendix B of Heise et al. (2022).
For any questions or comments, contact the lab at basclab@ucdavis.edu.
Heise, M. J., Mon, S. K., & Bowman, L. C. (2022). Utility of linear mixed effects models for event-related potential research with infants and children. Developmental Cognitive Neuroscience, 54, 101070. https://doi.org/10.1016/j.dcn.2022.101070