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Dropouts in the AB/BA crossover design
Author(s) -
Ho Weang Kee,
Matthews John N.S.,
Henderson Robin,
Farewell Daniel,
Rodgers Lauren R.
Publication year - 2012
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4497
Subject(s) - crossover , crossover study , statistics , computer science , mathematics , medicine , artificial intelligence , alternative medicine , pathology , placebo
Missing data arise in crossover trials, as they do in any form of clinical trial. Several papers have addressed the problems that missing data create, although almost all of these assume that the probability that a planned observation is missing does not depend on the value that would have been observed; that is, the data are missing at random (MAR). In many applications, this assumption is likely to be untenable; in which case, the data are missing not at random (MNAR). We investigate the effect on estimates of the treatment effect that assume data are MAR when data are actually MNAR. We also propose using the assumption of no carryover treatment effect, which is usually required for this design, to permit the estimation of a treatment effect when data are MNAR. The results are applied to a trial comparing two treatments for neuropathic pain and show that the estimate of treatment effect is sensitive to the assumption of MAR. Copyright © 2012 John Wiley & Sons, Ltd.