Advanced Multiple Imputation Methods to deal with Missing Data
13 April 2018.
1 day (approximately 6 hours of teaching).
Registration will start at 9am, the course will finish by 5pm.
This course is now fully booked.
This course aims to extend the application of multiple imputation methods to deal with missing data in complex analyses, including longitudinal models and clustered data.
By the end of the course participants will be able to explore advanced methods to deal with missing data when carrying out:
- longitudinal analyses (including survival analyses);
- analyses of "big data";
- analyses of clustered data.
Who the course is intended for
The course is intended for statisticians, health economists, epidemiologists and other researchers who are involved in performing statistical analyses of epidemiological datasets with missing data. Participants should be familiar with the concept of multiple imputation, and have used it in practice. Participants should be familiar with standard regression methods for dichotomous and continuous outcomes beyond the basic introductory level. Participants should also be familiar with using STATA as the software package for statistical analyses of the data.
This course builds on prior knowledge of multiple imputation for dealing with missing data, and extends this to the application of multiple imputation to longitudinal analyses, analyses of "big data" and analyses of clustered data.
The course will include:
- brief revision of theory and practice of multiple imputation in simple scenarios;
- dealing with missing data in longitudinal studies, including in survival analyses;
- use of multiple imputation in analysing "big data";
- application of multiple imputation to analyses of clustered data;
- interactive practical sessions for each of the above applications.
Please note: Practical sessions of this course will be held in a computer lab, so you will not need to bring a laptop. Stata 14 will be used during the course.
More information on course fees, fee waivers and reduced prices.
Bristol Medical School
39 Whatley Road
We provide morning and afternoon refreshment breaks, including tea and coffee, biscuits and fresh fruit.
If you have specific dietary needs we ask that you let us know in advance.
Lunch is not included. There are a range of local cafes and supermarkets nearby for students to purchase lunch.
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For further information please email firstname.lastname@example.org.