Handling Missing Data in Longitudinal Surveys
Venue: ESRI, Whitaker Square, Dublin 2
Time: 10.00 - 16.30
This is the first CLSI training course and is now fully booked, however further courses are being organised for later in the year and in 2014.
Course Summary
(the full programme for the course can be downloaded below)
Missing data, both as a result of attrition and item non-response, can introduce serious bias into longitudinal analyses. This short course will teach users of longitudinal data how to recognise types of missing data problems and practical ways of dealing with them.
The first day of the course will provide an overview of methods for adjusting for missing data, descriptions of missing data and their predictors in the UK birth cohort studies, plus introductions to the datasets to be used in the practical sessions on days two and three. The practical work will focus on multiple imputation, although weighting methods and joint models for the process of interest and the missingness mechanism will also be discussed. All the techniques will be demonstrated using real data from the UK birth cohort studies.
Course Level:
Advanced
Course Requirements:
Participants should have some familiarity with longitudinal data, a working knowledge of STATA and a good understanding of regression and logistic regression.
Course Duration:
3 days (9:30 to 16:30)
Course Fee:
€350
Location:
ESRI, Whitaker Square, Sir John Rogerson’s Quay, Dublin 2
Target Audience:
The course is designed for users of longitudinal data in general. It would be particularly appropriate for those who want to extend their skills as analysts of longitudinal data to take account, in a statistically principled way, the ubiquitous problems of missing data, arising both as a result of attrition and item non-response.
Course Tutors:
Prof. Ian Plewis joined the University of Manchester in 2007 as Professor of Social Statistics having previously worked at the Centre for Longitudinal Studies, Institute of Education, University of London where he was Professor of Longitudinal Research Methods in Education and where he now holds a visiting professorship.
Dr Jonathan Bartlett is a Lecturer in the Dept. of Medical Statistics at the London School of Hygiene and Tropical Medicine. He teaches the School's course on statistical analysis with missing data using multiple imputation and inverse probability weighting and his research centres on methods of multiple imputation which can be used in realistically complex settings.
Note: This is the first CLSI training course and is now fully booked, however further courses are being organised for later in the year and in 2014.