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")