Logistic Regression in R for Public Health and Psychology

Course Duration: 2 hours theory, 4 hours practice

What You'll Learn

Describe a data set from scratch using descriptive statistics and simple graphical methods as a first step for advanced analysis using R software
Interpret the output from your analysis and appraise the role of chance and bias as potential explanations
Run multiple logistic regression analysis in R and interpret the output
Evaluate the model assumptions for multiple logistic regression

1 Introduction to Logistic Regression

2 Odds and Odds Ratios

3 Additional Reading

4 Why Does Linear Regression Not Work with Binary Outcomes?

5 Odds Ratios and Examples from the Literature

6 Logistic Regression in R

7 Preparing the Data for Logistic Regression

8 Logistic Regression in R

9 How to Describe Data in R

10 Results of Cross Tabulation

11 Practice in R: Simple Logistic Regression

12 Feedback – Output and Interpretation from Simple Logistic Regression

13 Running Multiple Logistic Regression in R and Python

14 Assessing Model Fit