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Multiple imputation is used to impute country of birth from the SIPP into the SCF.
For the economic evaluation multiple imputation is used to impute missing data.
Yet, the multilevel methods required to achieve this are quite novel and multiple imputation is generally recommended for imputing sporadic missing values instead of systematically missing data.
Multiple imputation is a framework in which missing data are imputed or replaced with a set of plausible values.
Multiple imputation is a common approach for dealing with missing values in statistical databases.
Certainly, multiple imputation is an innovative approach over the traditional ones.
Multiple imputation is a statistical technique which uses available data to predict missing values.
The next step in multiple imputation is specification of the imputation model.
Before explaining what multiple imputation is, we consider it useful to study the mechanisms and patterns associated with missing data.
The first task that needs to be accomplished when carrying out multiple imputation is selection of the predictor variables.
Multiple imputation is becoming easier and more tempting to use thanks to the existence of different software packages.
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