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Practical Use of Multiple Imputation to Handle Missing Data in Stata

  • 15 hours
  • 2 day

Overview

On this two-day course you'll learn how to analyse data using multiple imputation, as well as the pitfalls and limitations of this technique.

This course is for researchers needing to analyse incomplete data.

There'll be an opportunity for you to discuss your own data and problem.

You'll be using Stata in practical sessions so you'll need to be familiar with this software before you attend.

This course is run by the Institute of Clinical Trials and Methodology (ICTM) at UCL.

Course content and structure

This course will cover:

  • an introduction to missing data and multiple imputation
  • imputation of a single incomplete variable
  • multivariate imputation using chained equations
  • analysis of multiply imputed data
  • compatible imputation and analysis models
  • multiple imputation in multilevel data
  • multiple imputation in data missing not at random
  • limitations of multiple imputation and reporting of analyses using multiple imputation

The course involves a series of lectures and computer practicals. 

Examples will be taken from the lecturers’ experiences, primarily relating to medical statistics.

You're welcome to bring your own data and problems. One session is dedicated to discussing these, and may include live analysis of some participants' data.

Entry requirements

You should be familiar with running Stata from the command line (i.e. not using menus) and be able to fit a regression model to complete data and produce simple graphs.

You don't need to have any prior knowledge of multiple imputation.

You'll need to bring your own laptop with Stata (version 12 or newer) installed. If you don't have Stata, contact the course administrator and they'll aim to provide you with a temporary copy.

Learning outcomes

By the end of this course you'll be able to:

  • appreciate the problems of missing data and the need for methods such as multiple imputation
  • explain how multiple imputation works
  • multiply impute data and analyse multiply imputed data
  • understand the assumptions underlying multiple imputation and the method's limits

Cost and concessions

The fees are:

  • standard - £360
  • UCL staff and students - £200
  • staff and students based at the ICTM - free

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Course team

Dr Tim Morris

Tim is a statistician interested in practical methods for improving the design and analysis of randomised trials and observational studies. He's based at the MRC Clinical Trials Unit at UCL, part of the Institute of Clinical Trials and Methodology.


Professor Ian White

an is a medical statistician with an interest in developing new methodology for design and analysis of clinical trials, meta-analysis and observational studies. He joined the MRC Clinical Trials Unit at UCL in 2017 after spending 16 years as a programme leader at the Medical Research Council's Biostatistics Unit in Cambridge.


Angela Wood

Angela is University Lecturer in Biostatistics in the Department of Public Health and Primary Care, at the University of Cambridge. She presents lectures on introductory statistics, descriptive statistics, strategies for analysis, analysis of clustered data and repeated measures, missing data, demographic methods and risk prediction.


Course information last modified: 20 Dec 2018, 13:28

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