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Practical use of multiple imputation to handle missing data in Stata<https://www.ucl.ac.uk/clinical-trials-and-methodology/education/short-courses/missing-data>
London, 11–12 Feb 2019
Course overview
The aim of this course is to provide participants with the ability to analyse their own data using multiple imputation and to be aware of the pitfalls and limitations of the technique. We will give plenty of practical examples from our own experience of analysing data in medical research. We welcome participants bringing their own data and problems, and one session is dedicated to discussion of how to handle missing data in some participants’ work. A tutorial<http://onlinelibrary.wiley.com/doi/10.1002/sim.4067/pdf> based on this course has appeared in Statistics in Medicine.
Course aims
• Explain the problems of missing data and the need for methods such as multiple imputation
• Explain how multiple imputation works, with a focus on ‘imputation by chained equations’
• Explain how multiply imputed data are analysed
• Enable participants to analyse data by multiple imputation in Stata using the commands mi impute chained and mi estimate
• Give participants an awareness of the assumptions underlying multiple imputation and of its limitations.
Target audience
The target audience for this course is researchers needing to analyse incomplete data:
• Attendees are expected to be familiar with running Stata from the command line (i.e. not using menus) at least to the level of fitting a regression model to complete data and producing simple graph
• No prior knowledge of multiple imputation is assumed.
• Participants should bring their own laptop computer with Stata 12 or newer installed. Participants without Stata should contact the course administrator and we will aim to provide a temporary copy.
The course would also be suitable as a refresher for people familiar with multiple imputation using Stata’s ice and mim commands wanting to learn about the newer mi impute chained and mi estimate.
Software required
All participants will need their own laptop running Stata 12 or newer, as we will be using mi impute chained (which was new in Stata 12).
Fees
£360, except:
• Students: £200
• UCL Staff: £200
The course fees cover copies of the course lectures and practical sessions, lunch and tea/coffee breaks. Attendees are advised to arrange their own travel and accommodation.
Facilitators
Ian White<http://www.ctu.mrc.ac.uk/about_us/senior_staff_profiles/ian_white/>, MRC Clinical Trials Unit at UCL
Angela Wood<http://www.phpc.cam.ac.uk/people/ceu-group/ceu-senior-academic-staff/angela-wood/>, University of Cambridge
Tim Morris<http://iris.ucl.ac.uk/iris/browse/profile?upi=TNMOR17>, MRC Clinical Trials Unit at UCL
Please contact Tufail Hussain if you have any queries: [log in to unmask]<mailto:[log in to unmask]>
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