Name: Survival Analysis in R for Public Health
Brand: Imperial College London
Availability: OnlineOnly
Rating: 4.5 (73 reviews)

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学生对 Imperial College London 提供的 Survival Analysis in R for Public Health 的评价和反馈

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329 个评分

课程概述

Welcome to Survival Analysis in R for Public Health! The three earlier courses in this series covered statistical thinking, correlation, linear regression and logistic regression. This one will show you how to run survival – or “time to event” – analysis, explaining what’s meant by familiar-sounding but deceptive terms like hazard and censoring, which have specific meanings in this context. Using the popular and completely free software R, you’ll learn how to take a data set from scratch, import it into R, run essential descriptive analyses to get to know the data’s features and quirks, and progress from Kaplan-Meier plots through to multiple Cox regression. You’ll use data simulated from real, messy patient-level data for patients admitted to hospital with heart failure and learn how to explore which factors predict their subsequent mortality. You’ll learn how to test model assumptions and fit to the data and some simple tricks to get round common problems that real public health data have. There will be mini-quizzes on the videos and the R exercises with feedback along the way to check your understanding. Prerequisites Some formulae are given to aid understanding, but this is not one of those courses where you need a mathematics degree to follow it. You will need basic numeracy (for example, we will not use calculus) and familiarity with graphical and tabular ways of presenting results. The three previous courses in the series explained concepts such as hypothesis testing, p values, confidence intervals, correlation and regression and showed how to install R and run basic commands. In this course, we will recap all these core ideas in brief, but if you are unfamiliar with them, then you may prefer to take the first course in particular, Statistical Thinking in Public Health, and perhaps also the second, on linear regression, before embarking on this one....

26 - Survival Analysis in R for Public Health 的 50 个评论（共 73 个）

创建者 Hương G P

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May 22, 2020

Highly recommended. This course is very constructive and is a good start for R beginner.

创建者 Sergio P

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Nov 7, 2019

Excellent course. Definitely a MUST DO if you would like to learn statistics in RStudio.

创建者 ITALO E S E S

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May 18, 2021

The course is very interesting and provides insight into the use of survival analysis.

创建者 Faisal A

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Jul 22, 2019

Very nice introductory course on survival analysis in R. Exercises were well designed.

创建者 LIANG Y

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Aug 24, 2020

What a great course it is!!! I could get the solid basic knowledge from the course.

创建者 Ruben C

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Jul 22, 2023

Great course to remember what I learned at university with applications in R

创建者 An T P

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Jun 17, 2023

This a good course for those who want to dive into survival analysis.

创建者 Anusha B

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Jun 15, 2020

Awesome course learned a lot from this entire series. Thank you!!!

创建者 Mohammad R W

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Dec 25, 2019

Take this course alongwith linear and logistic regression in R

创建者 Junwen Z

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Mar 15, 2020

Very good introduction course for survival analysis in R

创建者 Klorence W

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Dec 13, 2020

hope we could get some feedback on the final test

创建者 Sidney d S P B

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Jul 5, 2020

Excelent! Professor Alex Bottle is superb!

创建者 Amn A

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Jun 30, 2021

Amazing course overall. Learned a lot.

创建者 Ronpichai C

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May 24, 2020

Great course for survival analysis!!!!!

创建者 Jin C

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Jul 30, 2020

Nice lecture by the excellent lecturer

创建者 Jeffrey Y

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Mar 23, 2022

Excellent course and instructor

创建者 Jesús A O D

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May 4, 2020

Ecxellent, thak you, very much

创建者 Shoummo S G

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Jul 11, 2020

Excellent experience

创建者 Yasna P S

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Mar 4, 2020

Excellent course!

创建者 Pedro M

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Apr 16, 2020

Great course!!

创建者 fabien M

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Apr 23, 2020

Great course.

创建者 Shakil A S

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Feb 17, 2021

amazing!

创建者 Oleksandr T

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Aug 29, 2020

Nice course, the lecturer explains very clear.

Just there are problems with p-value decimals, as Rstudiro free provides only two, and even with variable formatting, I git .275. when the result from Rstudio pro was .278 This confuses many students. Assignments need to be in 2 decimals calculated at the free version of RStudio.