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Learning Statistical Models Through Simulation in R

B Bibliography

Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412.

Barr, D. J. (2013). Random effects structure for testing interactions in linear mixed-effects models. Frontiers in Psychology, 4, 328.

Barr, D. J. (2017). Generalizing over encounters: Statistical and theoretical considerations. In Oxford handbook of psycholinguistics. Oxford University Press. https://psyarxiv.com/mcrzu/

Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3), 255–278.

Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1–48.

Belenky, G., Wesensten, N. J., Thorne, D. R., Thomas, M. L., Sing, H. C., Redmond, D. P., Russo, M. B., & Balkin, T. J. (2003). Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: A sleep dose-response study. Journal of Sleep Research, 12(1), 1–12.

Clark, H. H. (1973). The language-as-fixed-effect fallacy: A critique of language statistics in psychological research. Journal of Verbal Learning and Verbal Behavior, 12(4), 335–359.

Coleman, E. B. (1964). Generalizing to a language population. Psychological Reports, 14(1), 219–226.

DeBruine, L., & Barr, D. J. (2020). Understanding mixed effects models through data simulation. Advances in Methods and Practice in Psychological Science. https://psyarxiv.com/xp5cy/

Judd, C. M., Westfall, J., & Kenny, D. A. (2012). Treating stimuli as a random factor in social psychology: A new and comprehensive solution to a pervasive but largely ignored problem. Journal of Personality and Social Psychology, 103, 54–69.

Lakens, D., Scheel, A. M., & Isager, P. M. (2018). Equivalence testing for psychological research: A tutorial. Advances in Methods and Practices in Psychological Science, 1, 259–269. https://journals.sagepub.com/doi/abs/10.1177/2515245918770963

Luke, S. G. (2017). Evaluating significance in linear mixed-effects models in r. Behavior Research Methods, 49, 1494–1502.

Matuschek, H., Kliegl, R., Vasishth, S., Baayen, H., & Bates, D. (2017). Balancing Type I error and power in linear mixed models. Journal of Memory and Language, 94, 305–315.

McElreath, R. (2020). Statistical Rethinking: A Bayesian course with examples in R and STAN. CRC Press.

Vanhove, J. (2021). Collinearity isn’t a disease that needs curing. Meta-Psychology, 5.

Yarkoni, T. (2019). The generalizability crisis. https://doi.org/10.31234/osf.io/jqw35