TRAINING

Data Science Intermediate

Multiple imputation of missing data

26 - 27 September 2023

pre-recorded lectures available from 19th September 2023

Lecturers

Paola Zaninotto and Andrea Aparicio Castro

Course description

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.

Learning objectives

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

Course Structure

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

Timetable

Date	Title
From 19^th 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 26^th September	10:00-11:30am	Live online Session 1 in either Stata or R
Wednesday 27^thSeptember	10:00-11:30am	Live online Session 2 in either Stata or R

Pre-requisite

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

Fee

Free.

Registration

https://www.eventbrite.co.uk/e/multiple-imputation-of-missing-data-tickets-477257137947

More information

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.