NSC-R Workshops: Multiple Imputation of Missing Values in R

Stef van Buuren

In this workshop we laerned why and how you can use the R package mice to solve missing data problems by means of multiple imputation. Multiple imputation is a generic approach to analyse incomplete data that reduces bias and increases precision.

To get an idea of what the workshop was about, you could read (in Dutch) this short and accessible overview of multiple imputation. Alternatively, you could check out the (English) Wikipedia page.

To install the R package mice , copy and paste the next line into your R Studio Editor and run it:

install.packages(“mice”)

Join this workshop meeting on Zoom by clicking this link

Stef van Buuren is Professor of Statistical Analysis of Incomplete Data at the University of Utrecht and Principal Scientist at the Netherlands Organisation for Applied Scientific Research TNO in Leiden. He invented the MICE algorithm for multiple imputation of missing data. Here you can find more details about Stef and his work.

Materials

The slides that accompanied Stef’s presentation.

Citation

For attribution, please cite this work as

Buuren (2022, April 28). NSC-R Workshops: Multiple Imputation of Missing Values in R. Retrieved from https://nscrweb.netlify.app/posts/2022-04-28-multiple-imputation-in-r/

BibTeX citation

@misc{buuren2022multiple,
  author = {Buuren, Stef van},
  title = {NSC-R Workshops: Multiple Imputation of Missing Values in R},
  url = {https://nscrweb.netlify.app/posts/2022-04-28-multiple-imputation-in-r/},
  year = {2022}
}