Handling Missing Data in R with MICE

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Winnipeg workshop: Handling missing data in R with mice


This site contains materials for the Biostatistics Workshop Handling missing data in R with mice the 45th Annual Meeting of the Statistical Society of Canada, dated Sunday, June 11, 2017, located in Winnipeg E3 - 270 (EITC).


Nearly all data analytic procedures in R are designed for complete data, and many will fail if the data contain missing values. Typically, procedures simply ignore any incomplete rows in the data, or use ad-hoc procedures like replacing missing values with some sort of “best value”. However, such fixes may introduce biases in the ensuing statistical analysis.

Multiple imputation is a principled solution for this problem. The aim of this workshop is to enable participants to perform and evaluate multiple imputation using the R package mice.


The workshop will consist of 5 sessions, each of which comprises a lecture followed by a computer practical using R:

  1. Session I: Introduction, issues raised by missing data, and towards a systematic approach
  2. Session II: Introduction to multiple imputation
  3. Session III: Multivariate missing data (joint model approach, chained equations)
  4. Session IV: Imputation in practice (large data sets, hierarchical data, non-linearities, interactions)
  5. Session V: After imputation, guidelines for analysis and reporting

How to prepare

Please remember to bring your own laptop computer and make sure that you have write-access to that machine (some corporate computers do not allow write access) or that you have the following software and packages pre-installed.

  1. Download and install the latest version of R from the R-Project website
  2. Download and install the most recent version of RStudio Desktop (Free License) from RStudio’s website. This is not necessary, per se, but it is highly recommended as RStudio delivers a tremendous improvement to the user experience of base R.
  3. Install the following packages: mice, and lattice

Workshop materials

  1. Lectures
  2. Handout
  3. Practical I
  4. Practical II
  5. Practical III
  6. Practical IV