Introduction/Overview

Comment from a recent participant:

“Our trainer was brilliant! Very knowledgeable and willing to go above and beyond to help us out … Good value for money too - a very wide range of topics covered.”

Imputation is filling in missing responses with usable data.

According to Osborne (2013), imputation “is not merely ‘making up data’. The act of estimating values and retaining cases in your analysis most often leads to more replicable findings as they are generally closer to the actual population values than analyses that discard those with missing data.”

The course explores the pros and cons of several imputation methods from simplistic to sophisticated. The course presents the debates in the literature and includes real life examples. The course does not focus on specific software but rather on the decisions to be made in choosing an implementing an appropriate imputation method. Breakout sessions will help to put learning into practice.

Course requirements

Participants need to be familiar with confidence intervals, the terms standard error and sampling variance, and regression analysis.

Topics

The course covers:

• Item missing data
• Missing data acronyms
• Why use imputation?
• Simplistic methods: deductive imputation, mean imputation and random imputation
• More effective simplistic methods: predicted regression imputation, stochastic regression imputation and hot-deck imputation
• Sophisticated methods: Introductions to the concepts of inverse probability weighting, maximum likelihood analysis and multiple imputation
• The pros and cons of each method are discussed
• Real life examples are included as well as suggestions for software

Who will benefit

Both participants who want to use imputation strategies on their data and those participants who want knowledge of imputation methods for critiquing others’ work.

Learning objectives

By the end of the course, participants will:

• Have knowledge of a variety of imputation methods and the pros and cons of each
• Have an awareness of how each method works
• Be able to make informed choices about which particular imputation method is best for their data

Course tutor

Dr Pamela Campanelli is a Survey Methods Consultant and runs The Survey Coach business. She is also a Chartered Statistician and Fellow of the Academy of Social Sciences. She has worked at the University of Michigan, the U.S. Bureau of the Census, ISER at the University of Essex, and NatCen Social Research. She has both led and been a team member on ESRC grants (one on survey nonresponse and one on measurement error in mixed mode surveys). She regularly teaches short courses in the UK and abroad for government departments, survey research companies, universities, as well as for various other institutions and businesses. She believes in delivering courses that are lively and engaging and foster an informal and interactive atmosphere.

  This course contributes 6 hours to the MRS CPD programme