The issue of missing data may arise for researchers who deal with data gathering problems. Different methods of missing data imputation have been proposed to deal with such problems. The Bayesian ...

Rubin & Schenker (1986) proposed the approximate Bayesian bootstrap, a two-stage resampling procedure, as a method of creating multiple imputations when missing data are ignorable. Kim (2002) showed ...

When census-takers can’t reach anyone at a particular address or obtain information about occupants in other ways, they sometimes use a last-resort statistical technique called “imputation” to fill in ...