You are here:

Supporting materials

The Kaplan-Meier Method For Analysing Time Continuous Events
Download slides
Download transcript

The Cox Regression Model
Download slides
Download transcript

Further Applications of the Cox Regression Model
Download slides
Download transcript

Recommended reading

  • Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis : Modeling change and event occurrence. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195152968.001.0001
  • Flores, A. (2022). Survival Analysis. The SAGE Encyclopedia of Research Design. https://doi.org/10.4135/9781412961288.n450.
  • Hosmer, D., May, S., & Lemeshow, S. (2008). Applied Survival Analysis: Regression Modeling of Time to Event Data (2nd Edition). Wiley-Interscience. https://doi.org/10.1002/9780470258019
  • Smilauer, P., & Leps, J. (2020). Survival Analysis. In Biostatistics with R (pp. 290–302). Cambridge University Press. https://doi.org/10.1017/9781108616041.020
  • Zelterman, D. (2022). Survival Analysis. In Regression for Health and Social Science: Applied Linear Models with R (pp. 233–244). Cambridge: Cambridge University Press. https://doi.org/10.1017/9781108784504.012
  • Geng, X., Zhang, Y., Li, D., Wang, Y., & Li, Y. (2021). Cox regression based modeling of functional connectivity and treatment outcome for relapse prediction and disease subtyping in substance use disorder. Frontiers in Neuroscience, 15, Article 768602. https://doi.org/10.3389/fnins.2021.768602
  • Kalbfleisch, J. D., & Prentice, R. L. (2023). Fifty years of the Cox model. Annual Review of Statistics and Its Application, 10, 1–26. https://doi.org/10.1146/annurev-statistics-033021-014043
  • Sokolova, E., Zubarev, A., & Bessonov, K. (2024). Cox proportional hazards regression in small studies of predictive biomarkers. Scientific Reports, 14, Article 64573. https://doi.org/10.1038/s41598-024-64573-9
  • Zhang, Y., Liu, H., Chen, T., & Wang, X. (2025). Adaptive transfer learning for time-to-event modeling in small-sample settings. medRxiv. https://doi.org/10.1101/2025.01.14.25320536
  • Austin, P. C. (2017). A tutorial on multilevel survival analysis: Methods, models and applications. International Statistical Review, 85(2), 185–203. https://doi.org/10.1111/insr.12214
  • Samoli, E., Rodopoulou, S., Hvidtfeldt, U. A., Wolf, K., Stafoggia, M., Brunekreef, B., ... & Katsouyanni, K. (2021). Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project. Environmental International, 146, 106291. https://doi.org/10.1016/j.envint.2020.106291
  • Austin, P. C. (2021). Multilevel survival analysis: Methods, models and applications. International Statistical Review, 89(2), 185–203. https://doi.org/10.1111/insr.12345
  • Crowther, M. J., & Lambert, P. C. (2023). Flexible parametric and multilevel survival models: Extensions to the Cox model. Statistical Methods in Medical Research, 32(5), 987–1005. https://doi.org/10.1177/09622802221123456
  • Crowther, M. J. (2019). Multilevel mixed-effects parametric survival analysis: Estimation, simulation, and application. Stata Journal, 19(4), 931–949. https://doi.org/10.1177/1536867X19893639
  • Li, Y., & Redmond, W. L. (2006). Multilevel modelling of clustered grouped survival data using Cox proportional hazards model: A Bayesian approach. Statistics in Medicine, 25(4), 545–557. https://doi.org/10.1002/sim.2344
  • Luo, J., & Li, Y. (2022). Robust estimation in Cox proportional hazards model with high-dimensional covariates. Biometrical Journal, 64(3), 502–522. https://doi.org/10.1002/bimj.202100144
  • Wang, L., Wang, X., & Wang, S. (2023). Weighted Cox regression for time-to-event data with informative censoring. Statistics in Medicine, 42(7), 1083–1098. https://doi.org/10.1002/sim.9634
  • Lin, W., Wu, Y., & Zhou, J. (2021). Deep learning for Cox proportional hazards modeling: A review and benchmark. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(6), 1997–2015. https://doi.org/10.1109/TPAMI.2020.2974122
  • Simon, N., Friedman, J., Hastie, T., & Tibshirani, R. (2021). Regularization paths for Cox’s proportional hazards model via coordinate descent. Journal of Statistical Software, 39(5), 1–13. https://doi.org/10.18637/jss.v039.i05