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Courses>Programming Languages>Survival Analysis in R
Data ScienceSurvival Analysis in R
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:intermediate
Updated:05 March 2024
Published:08 September 2022
Similar courses
Opportunities
Courses>Programming Languages>Survival Analysis in R
Survival Analysis in R
4 Hours
9190 students
Syllabus
In the first chapter, we introduce the concept of survival analysis, explain the importance of this topic, and provide a quick introduction to the theory behind survival curves. We discuss why special methods are needed when dealing with time-to-event data and introduce the concept of censoring. We also discuss how we describe the distribution of the elapsed time until an event.
In this chapter, we will look into different methods of estimating survival curves. We will discuss the Kaplan-Meier estimate and the Weibull model as tools for survival curve estimation and learn how to communicate those results through visualization.
In this chapter, we will learn how to estimate and visualize a Weibull model to learn about the effects of covariates on the time-to-event outcome.
In the last chapter, we learn how to compute and interpret Cox models to understand why they are useful and how they differ from Weibull models.
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Careertail
Courses>Programming Languages>Survival Analysis in R
Data ScienceSurvival Analysis in R
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:intermediate
Updated:05 March 2024
Published:08 September 2022
Similar courses
Opportunities
Courses>Programming Languages>Survival Analysis in R
Survival Analysis in R
4 Hours
9190 students
Syllabus
In the first chapter, we introduce the concept of survival analysis, explain the importance of this topic, and provide a quick introduction to the theory behind survival curves. We discuss why special methods are needed when dealing with time-to-event data and introduce the concept of censoring. We also discuss how we describe the distribution of the elapsed time until an event.
In this chapter, we will look into different methods of estimating survival curves. We will discuss the Kaplan-Meier estimate and the Weibull model as tools for survival curve estimation and learn how to communicate those results through visualization.
In this chapter, we will learn how to estimate and visualize a Weibull model to learn about the effects of covariates on the time-to-event outcome.
In the last chapter, we learn how to compute and interpret Cox models to understand why they are useful and how they differ from Weibull models.
Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot