Bmc Med Res Methodol
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Bmc Med Res Methodol · Oct 2012
Randomized Controlled TrialAn exploration of the missing data mechanism in an Internet based smoking cessation trial.
Missing outcome data are very common in smoking cessation trials. It is often assumed that all such missing data are from participants who have been unsuccessful in giving up smoking ("missing=smoking"). Here we use data from a recent Internet based smoking cessation trial in order to investigate which of a set of a priori chosen baseline variables are predictive of missingness, and the evidence for and against the "missing=smoking" assumption. ⋯ Those conducting smoking cessation trials, and wishing to perform an analysis that assumes the data are MAR, should collect and incorporate baseline variables into their models that are thought to be good predictors of missing data in order to make this assumption more plausible. However they should also consider the possibility of Missing Not at Random (MNAR) models that make or allow for less extreme assumptions than "missing=smoking".