A note on imputing squares via polynomial combination approach

Publication date

2022-11

Authors

Cai, MingyangISNI 0000000517912281
Vink, GerkoORCID 0000-0001-9767-1924ISNI 0000000394871968

Editors

Advisors

Supervisors

Document Type

Article
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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