R for Health Data Science
Preface
- Why read this book
- Contributors
About the Authors
I Data wrangling and visualisation
1 Why we love R
2 R basics
3 Summarising data
4 Different types of plots
5 Fine tuning plots
II Data analysis
6 Working with continuous outcome variables
7 Linear regression
8 Working with categorical outcome variables
9 Logistic regression
10 Time-to-event data and survival
III Workflow
11 The problem of missing data
12 Notebooks and Markdown
13 Exporting and reporting
14 Version control
15 Encryption
Appendix
Published with bookdown

R for Health Data Science

Chapter 6 Working with continuous outcome variables

Continuous data can be measured.
Categorical data can be counted.