  Missing data are ubiquitous in medical research. Although there is increasing
guidance on how to handle missing data, practice is changing slowly and
misapprehensions abound, particularly in observational research. We present a
practical framework for handling and reporting the analysis of incomplete data
in observational studies, which we illustrate using a case study from the Avon
Longitudinal Study of Parents and Children. The framework consists of three
steps: 1) Develop an analysis plan specifying the analysis model and how
missing data are going to be addressed. An important consideration is whether a
complete records analysis is likely to be valid, whether multiple imputation or
an alternative approach is likely to offer benefits, and whether a sensitivity
analysis regarding the missingness mechanism is required. 2) Explore the data,
checking the methods outlined in the analysis plan are appropriate, and conduct
the pre-planned analysis. 3) Report the results, including a description of the
missing data, details on how the missing data were addressed, and the results
from all analyses, interpreted in light of the missing data and the clinical
relevance. This framework seeks to support researchers in thinking
systematically about missing data, and transparently reporting the potential
effect on the study results.
