Methods for handling missing data
This chapter begins by describing helpful typologies of missing data based on pattern and non-response mechanisms. It then summarizes a collection of commonly used but imperfect methods for dealing with missing data at the analysis stage. Three more rigorous methods, maximum likelihood, multiple imputation, and weighting, are also considered.
Keywords: missing data, hot-deck imputation, likelihood methods, Bayesian inference, multiple imputation
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