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DataCamp Survival Analysis in R SURVIVAL ANALYSIS IN R Survival Analysis / Time-to- Event Analysis in R Heidi Seibold Statistician at LMU Munich DataCamp Survival Analysis in R The term survival analysis DataCamp Survival Analysis in R

  1. DataCamp Survival Analysis in R SURVIVAL ANALYSIS IN R Survival Analysis / Time-to- Event Analysis in R Heidi Seibold Statistician at LMU Munich

  2. DataCamp Survival Analysis in R The term survival analysis

  3. DataCamp Survival Analysis in R The term survival analysis

  4. DataCamp Survival Analysis in R The term survival analysis

  5. DataCamp Survival Analysis in R The term survival analysis

  6. DataCamp Survival Analysis in R Data sets we will be using GBSG2 : time to death of 686 breast cancer patients data(GBSG2, package = "TH.data") UnempDur : time to re-employment of 3343 unemployed patients data(UnempDur, package = "Ecdat") Pro tip : to learn about a dataset in R, use the help function help(UnempDur, package = "Ecdat")

  7. DataCamp Survival Analysis in R SURVIVAL ANALYSIS IN R Let's practice!

  8. DataCamp Survival Analysis in R SURVIVAL ANALYSIS IN R Why do we need special methods for time-to-event data? Heidi Seibold Statistician at LMU Munich

  9. DataCamp Survival Analysis in R Why survival analysis Times are always positive Different measures are of interest Censoring almost always an issue

  10. DataCamp Survival Analysis in R Why survival analysis Times are always positive Different measures are of interest Censoring almost always an issue

  11. DataCamp Survival Analysis in R Why survival analysis Times are always positive Different measures are of interest Censoring almost always an issue

  12. DataCamp Survival Analysis in R Creating Surv objects time <- c(5, 6, 2, 4, 4) event <- c(1, 0, 0, 1, 1) library("survival") Surv(time, event)

  13. DataCamp Survival Analysis in R R packages For all kinds of analyses: library("survival") For pretty visualisations: library("survminer") For more, see CRAN Task View: Survival Analysis

  14. DataCamp Survival Analysis in R SURVIVAL ANALYSIS IN R Let's practice!

  15. DataCamp Survival Analysis in R SURVIVAL ANALYSIS IN R The survival function Heidi Seibold Statistician at LMU Munich

  16. DataCamp Survival Analysis in R

  17. DataCamp Survival Analysis in R Survival analysis questions What is the probability that a breast cancer patient survives longer than 5 years? What is the typical waiting time for a cab? Out of 100 unemployed people, how many do we expect to have a job again after 2 months?

  18. DataCamp Survival Analysis in R Survival function THEORY INTERPRETATION S ( t ) = 1 − F ( t ) = P ( T > t ) Probability that duration is longer than t .

  19. DataCamp Survival Analysis in R Survival function THEORY INTERPRETATION S ( t ) = 1 − F ( t ) = P ( T > t ) Probability that duration is longer than t . Examples: Probability to survive beyond time point t . Probability that the cab takes more than t minutes to arrive.

  20. DataCamp Survival Analysis in R Survival function INTERPRETATION The median duration is t . Examples: The median survival time is 3.7 years. Median time until the cab arrives is 3.7 minutes.

  21. DataCamp Survival Analysis in R Survival function INTERPRETATION ^ 100 ⋅ ( t ) percent of durations are longer S than t . Examples: 37 percent of all patients survive longer than 4 years. 63 percent die within the first 4 years. Out of 100 cabs, 37 take more than 4 minutes to arrive.

  22. DataCamp Survival Analysis in R SURVIVAL ANALYSIS IN R Let's practice!

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