Statistical Learning with Python - Statistical Learning: 11.2 Proportional Hazards Model

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 0:41 The Log-Rank Test - Continued 2:14 Details of the Test Statistic 2:49 Log Rank Test: the Main Idea 3:45 The Final Result 5:17 Application to the Brain Cancer Dataset 6:56 Regression Models with a Survival Response 8:11 The Hazard Function 9:48 The Proportional Hazards Model 11:46 Proportional Hazards Model Continued 12:49 An Example