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Multiple imputation of missing values: Further update of ice, with an emphasis on categorical variables

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  • Patrick Royston

    ()
    (MRC Clinical Trials Unit and University College London)

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    Abstract

    Multiple imputation of missing data continues to be a topic of considerable interest and importance to applied researchers. In this article, the ice package for multiple imputation by chained equations (also known as fully con- ditional specification) is further updated. Special attention is paid to categorical variables. The relationship between ice and the new multiple-imputation system in Stata 11 is clarified.

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    Bibliographic Info

    Article provided by StataCorp LP in its journal Stata Journal.

    Volume (Year): 9 (2009)
    Issue (Month): 3 (September)
    Pages: 466-477

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    Handle: RePEc:tsj:stataj:v:9:y:2009:i:3:p:466-477

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    Related research

    Keywords: multiple imputation; chained equations; categorical variables; negative binomial distribution; ice; uvis; mi;

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    Cited by:
    1. Layte, Richard & Nolan, Anne, 2013. "Income-Related Inequity in the Use of GP Services: A Comparison of Ireland and Scotland," Papers WP454, Economic and Social Research Institute (ESRI).
    2. McGovern, Mark E., 2013. "Still Unequal at Birth: Birth Weight, Socioeconomic Status and Outcomes at Age 9," Working Paper 143356, Harvard University OpenScholar.
    3. White, Ian R. & Daniel, Rhian & Royston, Patrick, 2010. "Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2267-2275, October.
    4. Jaenichen, Ursula & Sakshaug, Joseph, 2012. "Multiple imputation of household income in the first wave of PASS," FDZ Methodenreport 201202_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Christoph Helbach, 2012. "The Interplay of Standardized Tests and Incentives – An Econometric Analysis with Data from PISA 2000 and PISA 2009," Ruhr Economic Papers 0356, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.

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