RiseUpp Logo
Educator Logo

Survival Analysis in R for Public Health

Master survival analysis techniques using R for public health research. Learn Kaplan-Meier plots and Cox regression analysis.

Master survival analysis techniques using R for public health research. Learn Kaplan-Meier plots and Cox regression analysis.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Statistical Analysis with R for Public Health Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.5

(311 ratings)

14,721 already enrolled

Instructors:

English

پښتو, বাংলা, اردو, 2 more

Powered by

Provider Logo
Survival Analysis in R for Public Health

This course includes

11 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Run and interpret Kaplan-Meier plots for survival analysis

  • Perform Cox regression modeling with multiple predictors

  • Assess model assumptions and fit in survival analysis

  • Handle real-world public health data challenges

  • Apply descriptive statistics and graphical methods effectively

Skills you'll gain

R Programming
Survival Analysis
Statistical Analysis
Cox Regression
Kaplan-Meier Analysis
Public Health Statistics
Data Analysis
Hazard Models
Time-to-Event Analysis
Statistical Modeling

This course includes:

0.8 Hours PreRecorded video

9 quizzes

Access on Mobile, Desktop, Tablet

FullTime access

Shareable certificate

Closed caption

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

Provided by

Certificate

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

icon-0icon-1icon-2icon-3icon-4

There are 4 modules in this course

This comprehensive course focuses on survival analysis techniques using R programming for public health applications. Students learn to perform time-to-event analysis, from basic Kaplan-Meier plots to advanced Cox regression models. The curriculum covers essential concepts like censoring, hazard functions, and model assumptions, using simulated hospital patient data for heart failure cases. Practical exercises emphasize data handling, statistical interpretation, and solving common challenges in public health data analysis.

The Kaplan-Meier Plot

Module 1 · 4 Hours to complete

The Cox Model

Module 2 · 2 Hours to complete

The Multiple Cox Model

Module 3 · 2 Hours to complete

The Proportionality Assumption

Module 4 · 2 Hours to complete

Fee Structure

Instructor

Alex Bottle
Alex Bottle

4.7 rating

413 Reviews

66,600 Students

6 Courses

Expert in Medical Statistics and Healthcare Quality

Prof. Alex Bottle is a Professor in Medical Statistics and co-director of the Dr Foster Unit at Imperial College London. His research is centered on measuring and understanding variations in healthcare quality and safety through the use of large databases. In addition to his research, Prof. Bottle teaches across various undergraduate and postgraduate programs, supervises and examines PhD students in fields such as surgery, cardiovascular risk, and digital health, and provides statistical training to the UK public sector.

Survival Analysis in R for Public Health

This course includes

11 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.5 course rating

311 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.