Missing data arise in almost all serious statistical analyses. Missing data are ubiquitous in social science research. It is important to consider the issues raised by missing data at the research design stage. As unplanned missing data inevitably introduce ambiguity into the inferences that can be drawn from a study, the design should be carefully scrutinised to minimise the scope for missing data to arise. Considerable care over this aspect of design will pay a substantial dividend when the study is analysed.
Inevitably, however, missing data will arise. Ambiguity in the analysis can be reduced if the chance of the data being missing depends only on observed data; the so-called missing at random scenario.
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Last date updated on July, 2020