Handling Missing Data in Administrative Studies:multiple imputation & inverse probability weighting
09/11/2017 - 10/11/2017
University of Southampton/ADRC-E
Professor James Carpenter
Intermediate (some prior knowledge)
View in Google Maps (SO17 1BJ)
Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Highfield, Southampton
Course number: ADRCE Training050 Carpenter
Course places are limited and registration by 2 November 2017 is strongly recommended.
Summary of Course
This ADRC-E course will consider the issues raised by missing data (both item and unit non-response) in studies using routinely collected data, for example electronic health records. Following a review of the issues raised by missing data, we will focus on two methods of analysis: multiple imputation and inverse probability weighting. We will also discuss how they can be used together. The concepts will be illustrated with medical and social data examples.
The course covers:
- Issues raised by missing data in the administrative setting: when is a complete records analysis sufficient?
- Shortcomings of ad-hoc methods
- Introduction to multiple imputation, including algorithms, common pitfalls, reporting and examples
- Introduction to inverse probability weighting for missing data, and its pros and cons viz-a-viz multiple imputation
- Combining inverse probability weighting and multiple imputation to improve robustness
- Strategies for large datasets, including the two-fold multiple imputation algorithm
- Discussion of participants’ data.
Professor James Carpenter
James is Professor of Medical Statistics at the London School of Hygiene and Tropical Medicine, and Programme Leader in Methodology at the MRC Clinical Trials Unit. He has a long-standing interest in longitudinal data and the issues raised by missing observations. He co-authored Multiple Imputation and its Application (Wiley, 2013) with Mike Kenward.
The course is aimed at quantitative researchers, who have an interest or experience in analysing administrative data. PhD students are also welcome. Detailed technical arguments will not be presented; instead the focus will be on concepts and examples, with participants encouraged to bring their own data for discussion.
This course includes computer workshops, using the statistical software package Stata. Full details of all commands will be given, so no previous experience with Stata is necessary, though it will inevitably be an advantage.
Practical experience using regression modelling (including survival data modelling) and preferably multilevel modelling.
(Draft Programme, subject to minor changes)
Thursday 9th November
9.00 – 9.30 Registration
9.30 – 9.45 Welcome and Introduction
9.45 – 10.45 Lecture 1: Introduction to issues raised by missing data in routine electronically collected databases
10.45 – 11.00 Coffee break
11.00 – 12.00 Practical 1: Missing data mechanisms
12.00 – 13.00 Lecture 2: Shortcomings of ad-hoc methods and introduction to Multiple Imputation
13.00 – 14.00 Lunch
14.00 – 15.00 Practical 2: Illustration of shortcomings of ad-hoc methods, simple MI, 1958 National Childhood Development Study data
15.00 – 15.30 Lecture 3a: More on MI: algorithms
15.30 – 15.45 Tea break
15.45 – 16.15 Lecture 3b: More on multiple imputation: pitfalls and reporting
16.15 – 17.30 Practical 3: MI for the 1958 National Childhood Development Study
Friday 10th November
8.30 – 9.00 Review, and continuation of practical 3
9.00 – 10.00 Lecture 4: Inverse probability weighting for missing item and unit data
10.00 –11.00 Practical 4: Inverse probability weighting for routinely collected health data
11.00 – 11.15 Coffee break
11.15 – 12.30 Lecture 5: Combining MI and IPW to improve robustness
12.30 – 13.30 Lunch
13.30 – 14.30 Practical 5: Examples of combining MI and IPW
14.30 – 15.00 Lecture 6: Strategies for large datasets and the two-fold multiple imputation
15.00 – 15.15 Tea break
15.15 – 16.15 Practical 6: Putting large data strategies into practice
16.15 – 16.45 Discussion (including discussion of participants’ data)
Podcasts for some of our previous courses can be found at https://adrn.ac.uk/about/network/england/training-podcasts/
Our courses are very popular and are often oversubscribed. If you cannot attend a course you have registered for, it is essential to kindly notify us a minimum of 30 days in advance so that your place can be released for another attendee. Details of our cancellation policy are here: http://store.southampton.ac.uk/help/?HelpID=1 . Please see our full course list here: http://store.southampton.ac.uk/browse/product.asp?compid=1&modid=5&catid=113.
The fee per day is:
1. £30 - For UK registered postgraduate students
2. £60 - For staff at UK academic institutions, Research Council UK funded researchers, UK public sector staff and staff at UK registered charity organisations
3. £220 - For all other participants
4. Free Place for ADRC-E/ADRN/ADS staff
All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.
Website and registration:
Nonresponse , Missing data, Imputation, Weighting, Regression Methods, Multiple imputation, inverse probability weighting, survey data, administrative data
Related publications and presentations: