A case study on the use of multiple imputation

Abstract

Multiple imputation is a relatively new technique for dealing with missing values on items from survey data. Rather than deleting observations for which a value is missing, or assigning a single value to incomplete observations, one replaces each missing item with two or more values. Inferences then can be made with the complete data set. This paper presents an application of multiple imputation using the 1987-1988 National Survey of Families and Households. We impute several binary indicators of whether the respondent's elderly mother/mother-in-law is married. Descriptive statistics are then presented for the sample of adult children with an unmarried mother or mother-in-law. © 1995 Population Association of America.