Skip to content

amices/Winnipeg

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Overview

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).

Motivation

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.

Contents

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
  • You can simply install packages from within RStudio by navigating to Tools > Install Packages in the upper menu and entering mice, lattice into the Packages field. Make sure that the button Install dependencies is selected. Once done, click Install and you’re all set.
  • Or, from within R or RStudio, copy, paste and enter the following code in the console window (by default the top-right window in RStudio / the only window in R):
install.packages("mice")
install.packages("lattice")

Workshop materials

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

About

Handling Missing Data in R with MICE

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages