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HANDLING MISSING OUTCOME DATA IN RANDOMISED TRIALS
MRC BIOSTATISTICS UNIT, CAMBRIDGE
14-15 March 2012
Lecturers: Ian White, Simon Bond, Shaun Seaman, Adrian Mander, James Wason.
Please see http://www.mrc-bsu.cam.ac.uk/HTMRmiss/ for more details and
online registration form.
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COURSE AIMS
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Review some popular ways to analyse trials with missing data,
focussing on the assumptions underlying them
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Discuss what assumptions may be plausible and how one should
decide this in particular trials
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Describe the theory for mixed models analysis of incomplete data,
how they should be implemented, and what are the pitfalls
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Demonstrate how to analyse data using mixed models and multiple
imputation in Stata, R and SAS
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Discuss the advantages and disadvantages of the two methods
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Discuss the different issues involved in handling missing baselines
The workshop will provide practising statisticians with the necessary
practical skills to handle missing data in their analyses, and in
particular to move beyond the use of complete-case analysis and last
observation carried forward analysis. We will focus on trials with
quantitative outcomes, and also consider binary outcomes but not
time-to-event outcomes.
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TARGET AUDIENCE
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Statisticians who analyse clinical trials with missing outcome data.
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Participants are asked to bring their own laptops with their
preferred statistical software (R, SAS or Stata).
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COSTS
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Student £100
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Public sector £200
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Commercial £400
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