Missing data

1 post

• Why linear mixed-effects models are probably not the solution to your missing data problems

  Jul 9, 2020 · 9 min read · R

  Linear mixed-effects models are often used for their ability to handle missing data using maximum likelihood estimation. In this post I will present a simple example of when the LMM fails, and illustrate two MNAR sensitivity analyses: the pattern-mixture method and the joint model.