Chapter 9 Multiple Imputation of Missing Data
In this chapter, you will learn:
- Missing data concepts and terminology;
- How to create multiply imputed datasets; and
- How to carry out the following analyses accounting for missing data via multiple imputation:
- Descriptive statistics;
- Linear regression;
- Binary logistic regression; and
- Cox proportional hazards regression.
This chapter assumes that you have read the chapters on these statistical analysis methods.
To use the code in this chapter, first load tidyverse
and Functions_rmph.R
(downloadable from RMPH Resources).
library(tidyverse)
source("Functions_rmph.R")