Imputation Methods for Single Variables

Seppo Laaksonen

Chapter 12 in Survey Methodology and Missing Data, 2018, pp 171-195 from Springer

Abstract: Abstract This chapter considers imputation methods for single variables. Naturally, it may be necessary to impute the values of several variables in each dataset and to carry out several imputations for each dataset. It is essential to understand the basics of Chap. 11 , which presents the starting point for imputation methods. It is helpful to look at that chapter for the core terms, but an important question is also why one should, or should not, use imputation. Before answering this question, it is necessary to analyse the missingness and the reasons for it thoroughly. Then again, it is good to remember that the imputation methodology always depends on the case; thus, each variable should be separately imputed even though the principles of the method used can be similar. Successful imputation therefore is ‘tailored’ to the specific case, and the best results are obtained if the ‘imputation team’ has sound knowledge of the basis of the data and its quality.

Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-79011-4_12

Ordering information: This item can be ordered from
http://www.springer.com/9783319790114

DOI: 10.1007/978-3-319-79011-4_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().