Multiple Imputation for Missing Data

Course dates

12 April 2018.

Course duration

1 day (approximately 6 hours of teaching including lectures, practicals and computer-based practicals).
Registration will start at 9am, the course will finish by 5pm.

Course tutors

Rosie CornishProfessor Kate Tilling(course organisers), Dr Jon Heron, Dr Rachael Hughes, Professor Margaret May and Professor Richard Morris. 

Course aims 

This course aims to provide a theoretical and practical introduction to multiple imputation methods to deal with missing data in simple (linear and logistic regression) situations.

Course objectives

The objectives of the course are to:

  • recognise the types and patterns of missing data, and when complete case analysis may be unbiased;
  • understand and apply multiple imputation methods to deal with missing data;
  • discuss how best to present multiple imputation methods and results in journal articles.

Who the course is intended for

The course is intended for statisticians, health economists, epidemiologists and other researchers who are, or will be, involved in performing statistical analyses of epidemiological datasets with missing data. 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.

Course outline

The course will include:    

  • introduction to the problems caused by missing data, complete case analyses and simple multiple imputation;
  • introduction to multiple imputation;
  • interactive practical session performing multiple imputation, including interactions and non-linear associations;
  • presenting multiple imputation methods and results in journal articles.  

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.

Recommended reading

Sterne et al Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 2009;338:b2393.    

White and Carlin. Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values. Stat. in Med. 29; 2920-2931, 2010.

Booking

Make a booking

Free - full, waiting list in operation.
Paid - places available.

All tutors are clearly extremely knowledgeable - great teachers.

Course feedback, March 2017

Course fee

£220

More information on course fees, fee waivers and reduced prices.

Course venue

Bristol Medical School
Canynge Hall
39 Whatley Road
Bristol
BS8 2PS
United Kingdom

Map and directions

Course refreshments

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. 

Accommodation

Information about accommodation in the area.

Contacts

For further information please email short-course@bristol.ac.uk.

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