Statistical Analysis with Missing data using multiple Imputation

Description:

In this course we begin by discussing the issues and problems raised by missing data, and introduce the key concepts required for classifying missing data mechanisms into one of three types. We then consider some of the frequently adopted ‘ad-hoc’ approaches for handling missing data, and discuss their limitations. Next, we introduce the method of multiple imputation, a practical and principled approach for handling missing data. Through computer practicals using Stata, participants will learn how to investigate missingness in their data and how to apply the statistical methods introduced in the course to realistic datasets.

Objectives

1. Provide an introduction to the issues raised by missing data, and the associated statistical jargon (missing completely at random, missing at random, missing not at random)
2. Illustrate the shortcomings of ad-hoc methods (eg mean imputation) for handling missing data
3. Introduce multiple imputation, as a practical and principled approach for handling missing data.

Prerequisites

Participants should be familiar with regression models, such as linear and logistic regression, and have a working knowledge of STATA.

The course is designed for researchers involved in social science and epidemiology who are faced with missing data in their analyses.

Recommended Reading

Schafer JL (1999) Multiple imputation: a primer. Statistical Methods in Medical Research 8; 3-15.
Sterne JAC, White IR, Carlin JB et al (2009) Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. British Medical Journal 338; b2393.

PROGRAMME

Mon 17th

9.45 – 10:00 Registration

10:00– 11:00 Lecture 1

11:00 – 11:30 Coffee/tea

11:30 – 13:15 Practical 1

13:15 – 14:15 Lunch

14:15 – 15:15 Lecture 2

15:15 – 15:45 Coffee/tea

15:45 – 17:30 Practical 2

Tue 18th

9:00 – 10:00 Lecture 3

10:00 – 10:30 Coffee/tea

10:30 – 12:15 Practical 3

12:15 – 13:15 Lunch

13:15 – 14:15 Lecture 4

14:15 – 16:00 Practical 4

All fees include event materials, lunch and tea breaks.  They do not include travel and accommodation costs.

Full refund for cancellation one month before the course, NO refunds can be made after this date.

Cost:

For UK registered postgraduate students £30 per day
£60.00
For staff at UK academic institutions, ESRC funded researchers and registered charity organisations £60 per day
£120.00
For all other participants £220 per day
£440.00

Website and registration:

http://go.soton.ac.uk/7b3

Region:

North West

Keywords:

Nonresponse , Missing data, Regression Methods, Stata

Related publications and presentations:

Nonresponse
Missing data
Regression Methods
Stata

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