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Bewertung und Feedback des Lernenden für Survival Analysis in R for Public Health von Imperial College London

266 Bewertungen
62 Bewertungen

Über den Kurs

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....



2. Juli 2020

Great course superb support and very clear professor. This course is a good motivator to continue to explore public health and statistics.


26. Aug. 2019

Good and practical introduction to survival analysis. I liked the emphasis on how to deal with practical data sets and data problems.

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26 - 50 von 62 Bewertungen für Survival Analysis in R for Public Health

von Faisal A

22. Juli 2019

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


24. Aug. 2020

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

von Anusha B

15. Juni 2020

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

von Mohammad R W

26. Dez. 2019

Take this course alongwith linear and logistic regression in R

von Junwen Z

15. März 2020

Very good introduction course for survival analysis in R

von Klorence W

14. Dez. 2020

hope we could get some feedback on the final test

von Sidney d S P B

5. Juli 2020

Excelent! Professor Alex Bottle is superb!

von amoulay

30. Juni 2021

Amazing course overall. Learned a lot.

von Ronpichai C

24. Mai 2020

Great course for survival analysis!!!!!

von Jin C

31. Juli 2020

Nice lecture by the excellent lecturer

von Jeffrey Y

23. März 2022

Excellent course and instructor

von Jesús A O D

4. Mai 2020

Ecxellent, thak you, very much

von Linh V M

6. Juli 2020

Very interesting and useful

von Shoummo S G

11. Juli 2020

Excellent experience

von Yasna P S

4. März 2020

Excellent course!

von Pedro M

16. Apr. 2020

Great course!!

von fabien M

23. Apr. 2020

Great course.

von Shakil A S

17. Feb. 2021


von Oleksandr T

30. Aug. 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.

von Leo H

4. Juni 2020

the use of R in the course was immersive and enjoyable, although the way some assignments were presented was inconsistent at times.

von Yan X

22. Nov. 2019

The final quiz is a little bit confusing ,pls provide detailed feedback on it so we can learn further even we did not pass it.

von Vajini A

30. Jan. 2021

Good intro, just wish there would be an intro to more advanced methods (e.g. time varying covariates).

von Pau G

17. März 2020

A fantasic intro to learn survival analysis where the time to the outcome is important

von Danielly X

23. Okt. 2021

The legends are wrong in english and portuguese, but the course is great!

von Basilio G

13. Mai 2019

High-quality, thoroughly-designed, hands-on, introductory course.