Survival Analysis in R for Public Health
Statistical Analysis with R for Public Health,
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.
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| Rating | 4.0★ based on 15 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 3-5 hours/week |
| Starts | Jul 3 (46 weeks ago) |
| Cost | $49 |
| From | Imperial College London via Coursera |
| Instructor | Alex Bottle |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Science Data Science Mathematics |
| Tags | Life Sciences Data Science Probability And Statistics Public Health |
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What people are saying
budding public health professionals
it uses assessments really well to test knowledge The course has been designed to cater to the requirement of budding public health professionals who want to enhance their skills beyond basic of epidemiology and biostatistics and gain a competitive edge.
correct answers generated by
The video transcripts were still raw (there needs to be an easy way for students like me who created cleaned video transcripts to upload them), two of the Week 4 quizzes would not accept the correct answers generated by the current software release (answer key needs to be updated), and the course itself needs someone to spend a few hours looking for bugs, typos, and doing polishing.
enhance their skills beyond
pls provide detailed feedback
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.
unnecessary discussion around multivariate
There are a lot of unnecessary discussion around multivariate regression and missing values that belong to a course on regression analysis and not survival analysis.
missing values that belong
must do if
Definitely a MUST DO if you would like to learn statistics in RStudio.
week 4 quizzes
current software release
too much text
There are few videos and too much text.
uses assessments really
health was worthwhile
Since I like taking notes from transcripts, it creates some inconvenience for me Overall, the series on Stats in Public Health was worthwhile, well-constructed, and very informative.
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An overview of related careers and their average salaries in the US. Bars indicate income percentile.
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Member of the Strategic Thinking Advisory Committee $60k
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Assistant Statistical Analyst 5 $75k
Biostatistician / Statistical Programmer $79k
Statistical Software Developer $120k
Master Statistical Analyst $125k
Quantitative and Statistical Analyst $143k
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| Rating | 4.0★ based on 15 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 3-5 hours/week |
| Starts | Jul 3 (46 weeks ago) |
| Cost | $49 |
| From | Imperial College London via Coursera |
| Instructor | Alex Bottle |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Science Data Science Mathematics |
| Tags | Life Sciences Data Science Probability And Statistics Public Health |
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