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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 2.6 based on 3 ratings
Length 5 weeks
Effort 3-5 hours/week
Starts Aug 3 (8 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

it only discusses

It only discusses very basic ideas such as the hazard function and the cox model which could be discussed in like 20 minutes.

competitive event models

This course does not discuss different types of survival model such as competitive event models.

discusses very basic

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.

like 20 minutes

too much text

There are few videos and too much text.

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Rating 2.6 based on 3 ratings
Length 5 weeks
Effort 3-5 hours/week
Starts Aug 3 (8 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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