References

Balka, Jeremy. n.d. “Making Statistics Make Sense.” In JB Statistics. https://www.jbstatistics.com/.
Berk, Richard, Lawrence Brown, Andreas Buja, Kai Zhang, and Linda Zhao. 2013. “Valid Post-Selection Inference.” The Annals of Statistics 41 (2): 802–37. https://doi.org/10.1214/12-AOS1077.
Breiman, Leo. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. https://doi.org/10.1023/A:1010933404324.
Genuer, Robin, Jean-Michel Poggi, and Christine Tuleau-Malot. 2010. “Variable Selection Using Random Forests.” Pattern Recognition Letters 31 (14): 2225–36. https://doi.org/10.1016/j.patrec.2010.03.014.
Genuer, Robin, Jean-Michel Poggi, and Christine Tuleau-Malot. 2015. VSURF: An R Package for Variable Selection Using Random Forests.” The R Journal 7 (2): 19–33. https://doi.org/10.32614/RJ-2015-018.
Greenland, Sander, Judea Pearl, and James M. Robins. 1999. “Causal Diagrams for Epidemiologic Research.” Epidemiology 10 (1): 37–48. https://doi.org/10.1097/00001648-199901000-00008.
Harrell, Frank E. 2015. Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. 2nd ed. Springer. https://doi.org/10.1007/978-3-319-19425-7.
Kalnins, Arturs, and Kendall Praitis Hill. 2025. “The VIF Score. What Is It Good for? Absolutely Nothing.” Organizational Research Methods 28 (1): 58–75. https://doi.org/10.1177/10944281231216381.
Marquardt, Donald W. 1970. “Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation.” Technometrics 12 (3): 591–612. https://doi.org/10.2307/1267205.
O’Brien, Robert M. 2007. “A Caution Regarding Rules of Thumb for Variance Inflation Factors.” Quality & Quantity 41 (5): 673–90. https://doi.org/10.1007/s11135-006-9018-6.
Strobl, Carolin, Anne-Laure Boulesteix, Achim Zeileis, and Torsten Hothorn. 2007. “Bias in Random Forest Variable Importance Measures: Illustrations, Sources and a Solution.” BMC Bioinformatics 8: 25. https://doi.org/10.1186/1471-2105-8-25.
Vatcheva, Kristina P., MinJae Lee, Joseph B. McCormick, and Mohammad H. Rahbar. 2016. “Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.” Epidemiology (Sunnyvale, Calif.) 6 (2): 227. https://doi.org/10.4172/2161-1165.1000227.
Zhu, Jin, Xueqin Wang, Liyuan Hu, et al. 2022. “Abess: A Fast Best-Subset Selection Library in Python and R.” Journal of Machine Learning Research 23 (202): 1–7. https://jmlr.org/papers/v23/21-1060.html.
Zhu, Junxian, Canhong Wen, Jin Zhu, Heping Zhang, and Xueqin Wang. 2020. “A Polynomial Algorithm for Best-Subset Selection Problem.” Proceedings of the National Academy of Sciences 117 (52): 33117–23. https://doi.org/10.1073/pnas.2014241117.