A note on imputing squares via polynomial combination approach
Publication date
2022-11
Editors
Advisors
Supervisors
Document Type
Article
Metadata
Show full item recordCollections
License
cc_by
Abstract
The polynomial combination (PC) method, proposed by Vink and Van Buuren, is a hot-deck multiple imputation method for imputation models containing squared terms. The method yields unbiased regression estimates and preserves the quadratic relationships in the imputed data for both MCAR and MAR mechanisms. However, Vink and Van Buuren never studied the coverage rate of the PC method. This paper investigates the coverage of the nominal 95% confidence intervals for the polynomial combination method and improves the algorithm to avoid the perfect prediction issue. We also compare the original and the improved PC method to the substantive model compatible fully conditional specification method proposed by Bartlett et al. and elucidate the two imputation methods’ characters.
Keywords
Missing data, Multiple imputation, Quadratic relation, Squared terms, Statistics and Probability, Statistics, Probability and Uncertainty, Computational Mathematics
Citation
Cai, M & Vink, G 2022, 'A note on imputing squares via polynomial combination approach', Computational Statistics, vol. 37, no. 5, pp. 2185-2201. https://doi.org/10.1007/s00180-022-01194-8