参考文献

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. https://doi.org/10.1016/j.jml.2007.12.005

Barr, D. J. (2013). Random effects structure for testing interactions in linear mixed-effects models. Frontiers in Psychology, 4, 328. https://doi.org/10.3389/fpsyg.2013.00328

Barr, D. J. (2017). Generalizing over encounters: Statistical and theoretical considerations. In Oxford handbook of psycholinguistics. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198786825.013.39

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. https://doi.org/10.1016/j.jml.2012.11.001

Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1–48. https://doi.org/10.18637/jss.v067.i01

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. https://doi.org/10.1046/j.1365-2869.2003.00337.x

Brown, V. A. (2021). An introduction to linear mixed-effects modeling in r. Advances in Methods and Practices in Psychological Science, 4(1). https://doi.org/10.1177/2515245920960351

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. https://doi.org/10.1016/S0022-5371(73)80014-3

Coleman, E. B. (1964). Generalizing to a language population. Psychological Reports, 14(1), 219–226. https://doi.org/10.2466/pr0.1964.14.1.219

DeBruine, L., & Barr, D. J. (2021). Understanding mixed effects models through data simulation. Advances in Methods and Practice in Psychological Science, 4(1). https://doi.org/10.1177/2515245920965119

Fiechter, J. L. (2024). Drawing generalizable conclusions from multilevel models: Commentary on van de calseyde and efendić (2022). Psychological Science, 35(6), 694–699. https://doi.org/10.1177/09567976241245411

Fraley, R. C., Gillath, O., & Deboeck, P. R. (2021). Do life events lead to enduring changes in adult attachment styles? A naturalistic longitudinal investigation. Journal of Personality and Social Psychology, 120(6), 1567–1606. https://doi.org/10.1037/pspi0000326

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(1), 54–69. https://doi.org/10.1037/a0028347

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. https://doi.org/10.3758/s13428-016-0809-y

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. https://doi.org/10.1016/j.jml.2017.01.001

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. https://doi.org/10.15626/MP.2021.2548

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