Borkovec, M., & Madin, N. (2019). ggparty: 'ggplot' Visualizations for the 'partykit' Package. R package version 1.0.0. Retrieved from https://github.com/martin-borkovec/ggparty
Bürkner, P.-C. (2017). brms: An R Package for Bayesian Multilevel Models Using Stan. Journal of Statistical Software, 80(1), 1-28. doi:10.18637/jss.v080.i01
Bürkner, P.-C. (2018). Advanced Bayesian Multilevel Modeling with the R Package brms. The R Journal, 10(1), 395-411. doi:10.32614/RJ-2018-017
Bürkner, P.-C. (2021). Bayesian Item Response Modeling in R with brms and Stan. Journal of Statistical Software, 100(5), 1-54. doi:10.18637/jss.v100.i05
Chang, W., Cheng, J., Allaire, J., Sievert, C., Schloerke, B., Xie, Y., Allen, J., McPherson, J., Dipert, A., & Borges, B. (2023). shiny: Web Application Framework for R. R package version 1.8.0. Retrieved from https://shiny.posit.co/
Chen, T., He, T., Benesty, M., Khotilovich, V., Tang, Y., Cho, H., ... Li, Y. (2024). xgboost: Extreme Gradient Boosting. R package version 1.7.7.1. Retrieved from https://github.com/dmlc/xgboost
Hothorn, T., Buehlmann, P., Dudoit, S., Molinaro, A., & Van Der Laan, M. (2006). Survival Ensembles. Biostatistics, 7(3), 355-373
Hothorn, T., Hornik, K., & Zeileis, A. (2006). Unbiased Recursive Partitioning: A Conditional Inference Framework. Journal of Computational and Graphical Statistics, 15(3), 651-674. doi:10.1198/106186006X133933
Iannone, R., & Roy, O. (2024). DiagrammeR: Graph/Network Visualization. R package version 1.0.11. Retrieved from https://rich-iannone.github.io/DiagrammeR/
Kuhn, M. (2008). Building Predictive Models in R Using the caret Package. Journal of Statistical Software, 28(5), 1–26. https://doi.org/10.18637/jss.v028.i05
Liaw, A., & Wiener, M. (2002). Classification and Regression by randomForest. R News, 2(3), 18--22
Milborrow, S. (2024). rpart.plot: Plot 'rpart' Models: An Enhanced Version of 'plot.rpart'. R package version 3.1.2. Retrieved from https://CRAN.R-project.org/package=rpart.plot
Molnar, C., Bischl, B., & Casalicchio, G. (2018). iml: An R package for Interpretable Machine Learning. JOSS, 3(26), 786. doi:10.21105/joss.00786
Neuwirth, E. (2022). RColorBrewer: ColorBrewer Palettes. R package version 1.1-3
Strobl, C., Boulesteix, A., Zeileis, A., & Hothorn, T. (2007). Bias in Random Forest Variable Importance Measures: Illustrations, Sources and a Solution. BMC Bioinformatics, 8(25). doi:10.1186/1471-2105-8-25
Strobl, C., Boulesteix, A., Kneib, T., Augustin, T., & Zeileis, A. (2008). Conditional Variable Importance for Random Forests. BMC Bioinformatics, 9(307). doi:10.1186/1471-2105-9-307
Thériault, R. (2023). rempsyc: Convenience functions for psychology. Journal of Open Source Software, 8(87), 5466. https://doi.org/10.21105/joss.05466
Therneau, T., & Atkinson, B. (2023). rpart: Recursive Partitioning and Regression Trees. R package version 4.1.23. Retrieved from https://cran.r-project.org/package=rpart
Wickham, H., François, R., Henry, L., Müller, K., & Vaughan, D. (2023). dplyr: A Grammar of Data Manipulation. R package version 1.1.4. Retrieved from https://dplyr.tidyverse.org
Zeileis, A., Hothorn, T., & Hornik, K. (2008). Model-Based Recursive Partitioning. Journal of Computational and Graphical Statistics, 17(2), 492-514. doi:10.1198/106186008X319331
Health CASCADE is a Marie Sklodowska-Curie Innovative Training Network funded by the European Union's Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement number 956501.
