Cro, S; Morris, TP; Kenward, MG; Carpenter, JR; (2016) Reference based sensitivity analysis for longitudinal trials with protocol deviation via multiple imputation. The Stata Journal , 16 (2) pp. 443-463.

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Abstract

Randomised controlled trials provide essential evidence for the evaluation of new and existing medical treatments. Unfortunately the statistical analysis is often complicated by the occurrence of protocol deviations, which mean we cannot always measure the intended outcomes for individuals who deviate, resulting in a missing data problem. In such settings, however one approaches the analysis, an untestable assumption about the distribution of the unobserved data must be made. To understand how far the results depend on these assumptions, the primary analysis should be supplemented by a range of sensitivity analyses, which explore how the conclusions vary over a range of different credible assumptions for the missing data. In this article we describe a new command, mimix, that can be used to perform reference based sensitivity analyses for randomised controlled trials with longitudinal quantitative outcome data, using the approach proposed by Carpenter, Roger, and Kenward (2013). Under this approach, we make qualitative assumptions about how individuals' missing outcomes relate to those observed in relevant groups in the trial, based on plausible clinical scenarios. Statistical analysis then proceeds using the method of multiple imputation.

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