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ppandora rings The figure shows our proposals for a hypothetical participant who attends only four of the nine visits (solid line).Possible ways to impute outcome measures at visit 9 for a hypothetical participant in the obesity trial who drops out after visit 4: main analysis (last value brought forward) and three sensitivity analyses (1 assumes participants lost to follow up return to baseline weight; 2 assumes 50% of weight regained, and 3 assumes intervention group regains a greater proportion of weight than controls)Fig 1 Possible ways to impute outcome measures at visit 9 for a hypothetical participant in the obesity trial who drops out after visit 4: main analysis (last value brought forward) and three sensitivity analyses (1 assumes participants lost to follow up return to baseline weight; 2 assumes 50% of weight regained, and 3 assumes intervention group regains a greater proportion of weight than controls)Open in new tabDiscussionThe ideal solution to the problems discussed here is to avoid missing data altogether. This is rarely practical, but missing data can be minimised by careful design and trial management,10 and in particular by attempting to follow up all participants.The obesity trial illustrated our strategy applied to a trial with a repeatedly measured outcome. Analysis choices are more limited in trials with a singly measured outcome pandora rings.
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