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.
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Laaksonen, S. (2018). Imputation Methods for Single Variables. In: Survey Methodology and Missing Data. Springer, Cham. https://doi.org/10.1007/978-3-319-79011-4_12
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DOI: https://doi.org/10.1007/978-3-319-79011-4_12
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