Abstract
Jill M. Montaquila and Chester H. Ponikowski
(1995) "An Evaluation Of Alternative Imputation
Methods," Proceedings of the Section on Survey Research
Methods, American Statistical Association.
Several imputation methods have been developed for
imputing missing responses. Often it is not clear which
imputation method is "best" for a particular
application. In choosing an imputation method, one should
consider several factors, including the types of estimates
that will be generated, the item nonresponse rates, the
nature of the missing data, and the availability of auxiliary
data that are correlated with the characteristic of interest
or with the response propensity. This paper compares the
performance of four commonly used imputation methods—nearest
neighbor hot-deck, random hot-deck, cell mean, and regression
imputation—in imputing missing benefit cost values for the
Employment Cost Index (ECI) survey. It is assumed the
nonrespondents are missing at random within classes. The
advantages and disadvantages of each method are described;
analytical and empirical results are presented.
Last Modified Date: July 19, 2008
|