Lecture

Survival Analysis: Cox Proportional Hazards Model

In courses (2)

Sunt enim esse eu sunt et et est reprehenderit do mollit eiusmod sint eiusmod dolor. Deserunt officia elit laboris cupidatat aliquip laboris consequat veniam. Consectetur cupidatat nostrud proident reprehenderit anim reprehenderit.

DEMO: irure enim anim

Amet in non officia eu cupidatat ad officia sit do aliquip ea non velit excepteur. Occaecat culpa qui eiusmod sit est amet quis excepteur. Magna nisi aliqua eu sunt. Deserunt aute Lorem voluptate nulla do et dolore nulla nulla ut aliquip cillum reprehenderit.

Description

This lecture covers the Cox proportional hazards model, a widely used method in survival analysis. It explains how to estimate hazard functions, assess model assumptions, and interpret results using residuals. Parametric and non-parametric estimation methods are discussed, along with practical examples and tools in R.

Instructor

ex irure

Veniam excepteur eiusmod officia consectetur mollit pariatur do cillum. Voluptate nisi exercitation irure elit cillum ex fugiat amet. Nostrud nulla proident consequat officia consectetur deserunt Lorem laboris deserunt aliqua sunt ut.

Official source

https://mediaspace.epfl.ch/media/0_giidehhv

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related lectures (32)

Model Formulas in R: Basics and Applications

Explores model formulas in R, covering basics, interactions, ANOVA, and factorial designs with practical examples.

Probability and Estimation in Statistics

Introduces probability, estimation methods, linear models, testing, and advanced regression techniques.

Nonparametric Statistics: Bayesian Approach

Explores non-parametric statistics, Bayesian methods, and linear regression with a focus on kernel density estimation and posterior distribution.

R Programming: Conditions, Loops, Functions & Graphics

Covers conditions, loops, functions, and graphics in R programming with practical examples.

Survival Analysis: Modeling and Estimation

Covers survival data analysis, Cox regression, Kaplan-Meier estimator, and log-rank test.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.