Survival Analysis / Time-to- Event Analysis in R Heidi Seibold - PowerPoint PPT Presentation

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 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")

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

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

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

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)

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

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

DataCamp Survival Analysis in R

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?

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

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.

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.

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.

Survival Analysis / Time-to- Event Analysis in R Heidi Seibold - PowerPoint PPT Presentation

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

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Classification Classification TNM classification Survival time Survival time Tumour size,

Parametric Survival Analysis So far, we have focused primarily on nonparametric and

Kaplan-Meier estimate Heidi Seibold Statistician at LMU Munich DataCamp Survival Analysis in R

RcmdrPlugin.survival : An R Commander Plug-in Package for Survival Analysis John Fox McMaster

Outline Counting processes Martingales Applications to survival analysis:

Nearest Neighbor and Kernel Survival Analysis Nonasymptotic Error Bounds and Strong

Survival analysis Niels Richard Hansen (Univ. Copenhagen) Statistics BI/E lecture March 18, 2009

Analysis of multistate data with thenetsurvival orcause specific survival :

Elements of survival analysis Gilbert Ritschard Department of Econometrics and Laboratory of

Survival analysis in R Niels Richard Hansen This note describes a few elementary aspects of

Survival analysis in R Niels Richard Hansen This note describes a few elementary aspects of

The Cox Model Heidi Seibold Statistician at LMU Munich DataCamp Survival Analysis in R Why use

Why use the Weibull model? Heidi Seibold Statistician at LMU Munich DataCamp Survival Analysis

Exploring the key genes and signaling transduction pathways related to the survival time of

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