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学生对 伦敦帝国学院 提供的 Survival Analysis in R for Public Health 的评价和反馈

202 个评分
50 条评论


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....


Jul 2, 2020

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

Aug 26, 2019

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


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

创建者 Anusha B

Jun 15, 2020

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

创建者 Mohammad R W

Dec 26, 2019

Take this course alongwith linear and logistic regression in R

创建者 Junwen Z

Mar 15, 2020

Very good introduction course for survival analysis in R

创建者 Klorence W

Dec 14, 2020

hope we could get some feedback on the final test

创建者 Sidney d S P B

Jul 5, 2020

Excelent! Professor Alex Bottle is superb!

创建者 Ronpichai C

May 24, 2020

Great course for survival analysis!!!!!

创建者 Jin C

Jul 31, 2020

Nice lecture by the excellent lecturer

创建者 Jesús A O D

May 4, 2020

Ecxellent, thak you, very much

创建者 Vũ M L

Jul 6, 2020

Very interesting and useful

创建者 Shoummo S G

Jul 11, 2020

Excellent experience

创建者 Yasna P S

Mar 4, 2020

Excellent course!

创建者 Pedro M

Apr 16, 2020

Great course!!

创建者 fabien M

Apr 23, 2020

Great course.

创建者 Oleksandr T

Aug 30, 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.

创建者 Leo H

Jun 4, 2020

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

创建者 Yan X

Nov 22, 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.

创建者 Pau G C

Mar 17, 2020

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

创建者 Basilio G

May 13, 2019

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

创建者 Jaideepsinh d

Jan 11, 2021

good in detailed

创建者 Sara K

Apr 17, 2020

It made learning very frustrating in every sense. Grading system has obviously some errors and nobody provides answers on Discussion forum. Final questions are formed in a way that was quite confusing to me and I never had that problem before also in much harder courses. Important things are not well explained including the mathematics behind. These is a lot of space for improving this course to make it better which is a pity because the course has some good moments as well.

创建者 NG, S L

Sep 4, 2020

The transcript is poorly made so I could not save notes without translating the transcript. There are bugs in quizzes (wrong model answer) too. Otherwise, I have gain much knowledge about Cox's regression.

创建者 Shengyang L

Feb 28, 2020

Got some setting error and not yet be fixed in week 4. The incorrect setting or answer set prevent the student from passing the quiz and proceed the course.

创建者 Jiasi H

Dec 7, 2019

It is a nice course! However, the video transcripts are very problematic. Since I like taking notes from transcripts, it creates some inconvenience for me

创建者 Xinyu W

Mar 10, 2020

not a lot of technical details are explained in this course thus a bit hard to understand

创建者 Ibrahim D K

Apr 16, 2020











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