Hands On Training

Survival Analysis in R

Name: Survival Analysis in R
Brand: Careervira
Price: 218 AUD
Availability: InStock
Rating: 1 (1 reviews)

via

DataCamp

Course Report

Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.

Visit Course Report

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Is it more likely that patients who are treated with the new drug will survive? How long does it take to find a job? What can I do to ensure my friends stay on the dance floor during my party? These questions can be answered best by analysing time-to-event data. To do this, we use certain statistical methods. This course introduces you to the basics of time-to–'event data analysis (also called survival analysis). This course will teach you how to use time-to-event data and how to interpret survivor curves.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Introduction to Regression in R

What You Will Learn

Learn how to deal with time-to-event data and how to compute, visualize and interpret survivor curves as well as Weibull and Cox models

Learn to work with time-to-event data

This course introduces basic concepts of time-to-event data analysis, also called survival analysis

Course Content

Expand all sections

Module 1: What is Survival Analysis?

Module 2: Estimation of survival curves

Module 3: The Weibull model

Module 4: The Cox Model

Course Instructors

Heidi Seibold

Statistician at LMU Munich

Heidi is a statistics postdoc at LMU Munich. Her research focus is on statistical methods for personalized medicine with the aim of improving treatment of patients. Heidi has collaborated on several ...