Logistic Regression in R for Public Health

Welcome to R for Public Health Logistic Regression! Why not just use logistic regression for public health purposes? Every data set needs to be taken into account in a specific way, but public health data sets have unique characteristics that require extra care. Simply put, they're a disaster. This course is hands-on, just like the others in the series, and will give you lots of practice using R on real-world, messy data. The course's worked example is identifying patients with diabetes based on a collection of patient characteristics.

Public health must take into account the viewpoint of the population as well as the perspective of the individual patient because the interpretation of the regression model's outputs can vary based on the viewpoint that you adopt. Nevertheless, a lot of the material taught in this course holds true for logistic regression when applied to any set of data, so you will be able to apply the concepts discussed in this course to logistic regression more generally as well.

The first two courses in the Statistics for Public Health specialization address topics like hypothesis testing, p values, and how to use R. This course builds on those topics. Before starting this course, you should examine Linear Regression for Public Health and Statistical Thinking for Public Health if you are not familiar with these concepts. You will enjoy expanding your knowledge and abilities in Statistics for Public Health: Logistic Regression for Public Health if you are currently proficient in these abilities.

What you will learn

• As a first step for advanced analysis using the R software, describe a data set from scratch using descriptive statistics and basic graphical techniques.
• Interpret the results of your analysis and consider the potential contributions of bias and chance.
• Interpret the results of multiple logistic regression analysis using R.
• Review the multiple logistic regression model assumptions in R.

Skill you will gain

• Logistic Regression
• R Programming

Instructor: Alex Bottle

Offered by: Imperial College London

Coursera rating: 4.8/5.0, 324 ratings

Enroll here: https://www.coursera.org/learn/logistic-regression-r-public-health