Data Science Intermediate

Multiple imputation of missing data
26 - 27 September 2023
pre-recorded lectures available from 19th September 2023
Paola Zaninotto and  Andrea Aparicio Castro

This online course is for anyone needing to address the issue of missing information in their quantitative data. It covers the most important principles of missing data analysis and how to effectively address the issues in analyses.

The aim is to develop skills in conducting multiple imputation analysis for cross-sectional data

By the end of this course you will be able to:

  • Identify different mechanisms of missing data
  • Use a multiple imputation method for dealing with missing data in cross-sectional studies
  • Specify perform and select models

There will be three pre-recorded lectures sessions and two 2.5-hour live computer practical sessions in R or Stata.



From 19th September 2023

Pre-recorded lectures available

Lecture 1

Introduction to missing data and ad hoc procedures

Lecture 2

Multiple imputation methods and assumptions

Lecture 3

Further considerations in multiple imputation of missing data

Tuesday 26th September


Live online Session 1 in either Stata or R

Wednesday 27th September


Live online Session 2 in either Stata or R

An understanding of regression models, quantitative data structures and types of variables.


This is a UKRI funded project offering rigorous training in longitudinal data science. Please note that this training is NOT available to undergraduate or masters students.