GESIS Training Courses

Scientific Coordination

André Ernst

Administrative Coordination

Claudia O'Donovan-Bellante
Tel: +49 621 1246-221

Applied Multiple Imputation

Online via Zoom
General Topics:
Course Level:
Software used:
Students: 300€
Academics: 450€
Commercial: 900€
Additional links
Lecturer(s): Dr. Kristian Kleinke, Maximilian Wächter

About the lecturer - Dr. Kristian Kleinke

About the lecturer - Maximilian Wächter

Course description

The purpose of this workshop is to (a) familiarize participants with the problems and pitfalls missing data pose to data analysts, (b) to discuss the pros and cons of various approaches to analyze incomplete empirical data (including multilevel data), (c) to demonstrate the application of the most important and widely used missing data tools in R (e.g. norm, pan, jomo, mice), so that having successfully completed that workshop, participants will be able to select and apply a missing data strategy that is well suited to their individual problem at hand.
Participants use their own computer / laptop and should have R ( and RStudio (desktop version, already installed. We will install additional R packages during the workshop. Participants are encouraged to bring their own data. There will be time during the workshop to discuss individual missing data problems!

Target group

The workshop is intended for students at the Master level and onwards who analyse data from all fields of social sciences (including clustered and panel data) that are affected by missing data.  

Learning objectives

You will learn how to „diagnose“ missing data problems and find suitable remedies. How to pick and apply a missing data strategy that is well suited for the problem at hand.
When to (multiply) impute missing data, and when better not.


Participants should have a basic understanding of statistical concepts and should be (at least somewhat) familiar with R.


Recommended readings

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