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Multiple Imputation of Squared Terms

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  • Gerko Vink
  • Stef van Buuren

Abstract

We propose a new multiple imputation technique for imputing squares. Current methods yield either unbiased regression estimates or preserve data relations. No method, however, seems to deliver both, which limits researchers in the implementation of regression analysis in the presence of missing data. Besides, current methods only work under a missing completely at random (MCAR) mechanism. Our method for imputing squares uses a polynomial combination. The proposed method yields both unbiased regression estimates, while preserving the quadratic relations in the data for both missing at random and MCAR mechanisms.

Suggested Citation

  • Gerko Vink & Stef van Buuren, 2013. "Multiple Imputation of Squared Terms," Sociological Methods & Research, , vol. 42(4), pages 598-607, November.
    • Handle: RePEc:sae:somere:v:42:y:2013:i:4:p:598-607
    DOI: 10.1177/0049124113502943
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    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Patrick Royston, 2005. "Multiple imputation of missing values: update," Stata Journal, StataCorp LP, vol. 5(2), pages 188-201, June.
    3. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 300-301, July.
    4. Patrick Royston, 2005. "Multiple imputation of missing values: Update of ice," Stata Journal, StataCorp LP, vol. 5(4), pages 527-536, December.
    5. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    6. Patrick Royston, 2005. "MICE for multiple imputation of missing values," United Kingdom Stata Users' Group Meetings 2005 02, Stata Users Group.
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