Published October 14, 2019
| Version v1
Lesson
Open
Tutorial: Intro to Discrete-Time Survival Analysis in R
Description
This tutorial provides the reader with a hands-on introduction to discrete-time survival analysis in R. Specifically, the tutorial first introduces the basic idea underlying discrete-time survival analysis and links it to the framework of generalised linear models (GLM). Then, the tutorial demonstrates how to conduct discrete-time survival analysis with the glm function in R, with both time-fixed and time-varying predictors. Some popular model evaluation methods are also presented. Lastly, the tutorial briefly extends discrete-time survival analysis with multilevel modelling (using the lme4 package) and Bayesian methods (with the brms package).
Notes
Since we continuously improve the tutorials, let us know via Github (https://github.com/Rensvandeschoot/Tutorials) if you discover mistakes, or if you have additional resources we can refer to.
Files
Files
(1.2 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:113c15ed5c62999a83b9fb675d4eff4f
|
42.9 kB | Download |
|
md5:708aad29d96e0c9e906fd49db306d77d
|
1.1 MB | Download |
Additional details
References
- Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48. doi:10.18637/jss.v067.i01
- Broström, G. (2018). eha: Event History Analysis. R package version 2.6.0. https://CRAN.R-project.org/package=eha
- Bürkner, P. (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
- Fox, J. (2003). Effect Displays in R for Generalised Linear Models. Journal of Statistical Software, 8(15), 1-27. http://www.jstatsoft.org/v08/i15/
- Long, JA. (2019). jtools: Analysis and Presentation of Social Scientific Data. R package version 2.0.1, https://cran.r-project.org/package=jtools
- Tutz, G., & Schmid, M. (2016). Modeling Discrete Time-to-Event Data (1st ed.). Springer New York. https://doi.org/10.1007/978-3-319-28158-2
- Welchowski, T., & Schmid, M (2018). discSurv: Discrete Time Survival Analysis. R package version 1.3.4. https://CRAN.R-project.org/package=discSurv
- Wickham, H. (2017). tidyverse: Easily Install and Load the 'Tidyverse'. R package version 1.2.1. https://CRAN.R-project.org/package=tidyverse