Statistical Learning: 11.1 Introduction to Survival Data and Censoring

Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing Trevor Hastie, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/people/trevor-j-hastie Robert Tibshirani, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/people/robert-tibshirani Jonathan Taylor, Professor Statistics at Stanford University - https://statistics.stanford.edu/people/jonathan-taylor You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion. You can choose to take the course in R (https://www.edx.org/course/statistica) or in Python (https://www.edx.org/learn/data-analysis-statistics/stanford-university-statistical-learning-with-python) For more information about courses on Statistics, you can browse our Stanford Online Catalog: https://stanford.io/3QHRi72 0:00 Introduction 0:01 Survival Analysis 1:16 Some of the big names in this field 2:48 Non-medical Examples 4:28 Survival and Censoring Times - Continued 5:12 Illustration 5:39 A Closer Look at Censoring 8:57 Estimating the Survival Curve Continued 10:59 The Kaplan-Meier Estimate: Example 11:31 Second Failure 12:18 Third Failure 12:58 Resulting KM Survival Curve 13:30 Kaplan-Meier Survival Curve for the BrainCancer Data