This book is designed to provide a guide for a short course on Survival Analysis, particularly related to the financial field.

The book is available at https://bookdown.org/sestelo/sa_financial.

Here is a view of the outline:

• Preface
• Programing language and software
• Main references and credits
• About the Author

1. Introduction
   1. What is Survival Analysis?
   2. Censoring
   3. Some Notation
   4. Survival and Hazard functions
   5. Relation between functions
   6. Some common distridution
2. Kaplan-Meier estimator
   1. Estimating survival
   2. Pointwise confidence interval
   3. Comparing survival curves
   4. Pros and cons of the Kaplan-Meier estimator
3. The Cox Proportional Hazards Model
   1. The semiparametric model
   2. Estimation
   3. Computing the Hazard Ratio
   4. Hypothesis testing
   5. Adjusting Survival Curves
   6. How to evaluate the PH assumption?
   7. Non-Proportional Hazards… and now what?
   8. Why Cox PH model is so popular? (pros of the model)
   9. Bonus track 1: Additive Cox model
   10. Bonus track 2: Machine Learning for estimating the Cox PH model
4. Joint Models for Longitudinal and Time-to-Event Data
   1. Linear Mixed Models
   2. Estimation of the Joint Model
   3. The JM package
5. Conditional Survival with condSURV
   1. Introduction
   2. Notation
   3. Estimation of the conditional survival
   4. The condSURV package
6. Spoiler!!
   1. Introduction
   2. Algorithm
   3. Aplication to real data

• Appendix A: Installation of R and RStudio
• Appendix B: Introduction to RStudio
• Appendix C: Introduction to R
• References

Of course, you are welcome to contribute to these notes. You can fork the repository, make your changes (or just edit a file in this repository using the `Edit button on Github if the change is simple enough) and open a pull request. I will try to be as responsive as possible in reviewing and accepting pull requests. Appreciate your contributions very much!

All material in this repository is licensed under CC BY-NC-SA 4.0.