During the meeting you will need some additional R libraries. Install them with
install.packages(c('ggplot2', 'survminer', 'dplyr'))
the first one help munging the data, the other one provides tool for survival analysis.
You can find needed data in the data/ directory.
In R/exercises.R one can view exercises prepared for the workshop and in R/answers.R we will be putting answers through the workshop.
A volounteer can come to tutor desk to fill the exercise in the answers sheet. For a properly solved exercises we have Why R? Foundation's powerbanks.
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M. Kosiński. R-ADDICT January 2017. Comparing (Fancy) Survival Curves with Weighted Log-rank Tests
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M. Kosiński. R-ADDICT January 2017. When You Went too Far with Survival Plots During the survminer 1st Anniversary
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A. Kassambara. STHDA December 2016. Survival Analysis Basics: Curves and Logrank Tests
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A. Kassambara. STHDA December 2016. Cox Proportional Hazards Model
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A. Kassambara. STHDA December 2016. Cox Model Assumptions
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M. Kosiński. R-ADDICT November 2016. Determine optimal cutpoints for numerical variables in survival plots
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M. Kosiński. R-ADDICT May 2016. Survival plots have never been so informative
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A. Kassambara. STHDA January 2016. survminer R package: Survival Data Analysis and Visualization.