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Missing data are ubiquitous in medical research. Although there is increasingguidance on how to handle missing data, practice is changing slowly andmisapprehensions abound, particularly in observational research. We present apractical framework for handling and reporting the analysis of incomplete datain observational studies, which we illustrate using a case study from the AvonLongitudinal Study of Parents and Children. The framework consists of threesteps: 1) Develop an analysis plan specifying the analysis model and howmissing data are going to be addressed. An important consideration is whether acomplete records analysis is likely to be valid, whether multiple imputation oran alternative approach is likely to offer benefits, and whether a sensitivityanalysis regarding the missingness mechanism is required. 2) Explore the data,checking the methods outlined in the analysis plan are appropriate, and conductthe pre-planned analysis. 3) Report the results, including a description of themissing data, details on how the missing data were addressed, and the resultsfrom all analyses, interpreted in light of the missing data and the clinicalrelevance. This framework seeks to support researchers in thinkingsystematically about missing data, and transparently reporting the potentialeffect on the study results.

Framework for the Treatment And Reporting of Missing data in Observational Studies: The TARMOS framework