PSI Journal Club: Limitations and Challenges with Mixed Model Repeated Measures (MMRM) Analysis
Moses Mwangi and Florian Lasch present their recent work on MMRM, with discussion lead by Geert Molenberghs.
Speaker: Michael O’Kelly (Principal Scientific Advisor, IQVIA)
Researchers in the last twenty years have come up with a snowstorm of ideas about how to interpret the results of clinical trials that have missing data. Michael O’Kelly summarises the landscape of ideas as he and his colleagues found it. A key change was the move from trying to “handle” missing data, to realising that missing data should be included in our understanding of clinical trial results. We can try to include missing data in our results by coarsening the outcome so as to include the missingness itself as part of that outcome; or by qualifying any estimate of treatment effect with sensitivity analyses; or by modelling some kind of counterfactual so as to attempt causal inference on a stratum of interest such as subjects who would have had no missing data. There are strong objections to each of these options, and the arguments continue. Michael will describe how in his own company, IQVIA, local Missing Data Superusers have improved the understanding of the issue of missing data, and also notes the strong co-operation in industry and academia in sharing methodologies for missing data. Current publicly available resources for statisticians will be summarised. Finally, Michael will talk about three key points: preventing missing data in clinical trials; how evidence from previous clinical trials can help give confidence in results when there is missing data; and the importance of clinical interpretability of results from trials with missing data.
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Moses Mwangi and Florian Lasch present their recent work on MMRM, with discussion lead by Geert Molenberghs.
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