Agresti, Alan. 2013. Categorical Data Analysis. 3rd ed. Wiley.
Fawcett, Tom. 2005. An Introduction to ROC Analysis. ELSEVIER.
Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. 2017. The Elements of Statistical Learning. 2nd ed. New York, NY: Springer.
James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning: With Applications in r. 1st ed. New York, NY: Springer.
Kuhn, Max, and Kjell Johnson. 2016. Applied Predictive Modeling. 1st ed. New York, NY: Springer.
Laerd. 2015. Statistical Tutorials and Software Guides.
Molnar, Christoph. 2020. Interpretable Machine Learning.
Moore, Dirk F. 2016. Applied Survival Analysis Using r. 1st ed. New York, NY: Springer.
Therneau, Terry, and Elizabeth Atkinson. 2019. An Introduction to Recursive Partitioning Using the RPART Routines. Boca Raton, Florida: Chapman; Hall/CRC.

  1. The related probit regression link function is \(f(E(Y|X)) = \Phi^{-1}(E(Y|X)) = \Phi^{-1}(\pi)\). The difference between the logistic and probit link function is theoretical, and the practical significance is slight. You can safely ignore probit.↩︎

  2. Notes from Machine Learning Mastery↩︎

  3. See neat discussion in Note section of Surv() help file.↩︎


  5. This formulation is derived from the relationship between the survival function to a baseline survival, \(S(t) = S_0(t)^\exp{Xb}\). See German Rodriguez’s course notes.↩︎

  6. Full discussion on Rens van de Schoot.↩︎