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The Multiple Adaptations of Multiple Imputation

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  • Reiter, Jerome P.
  • Raghunathan, Trivellore E.

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  • Reiter, Jerome P. & Raghunathan, Trivellore E., 2007. "The Multiple Adaptations of Multiple Imputation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1462-1471, December.
  • Handle: RePEc:bes:jnlasa:v:102:y:2007:m:december:p:1462-1471
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    Citations

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    Cited by:

    1. Woodcock, Simon D. & Benedetto, Gary, 2009. "Distribution-preserving statistical disclosure limitation," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4228-4242, October.
    2. Mauro Mediavilla Bordalejo, 2010. "Las becas y ayudas al estudio como elemento determinante de la continuidad escolar en el nivel secundario post-obligatorio. Un análisis de sensibilidad a partir de la aplicación del Propensity Score M," Investigaciones de Economía de la Educación volume 5,in: María Jesús Mancebón-Torrubia & Domingo P. Ximénez-de-Embún & José María Gómez-Sancho & Gregorio Gim (ed.), Investigaciones de Economía de la Educación 5, edition 1, volume 5, chapter 29, pages 561-582 Asociación de Economía de la Educación.
    3. Joseph W. Sakshaug & Trivellore E. Raghunathan, 2014. "Generating synthetic microdata to estimate small area statistics in the American Community Survey," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(3), pages 341-368, June.
    4. Yi Qian & Hui Xie, 2013. "Drive More Effective Data-Based Innovations: Enhancing the Utility of Secure Databases," NBER Working Papers 19586, National Bureau of Economic Research, Inc.
    5. repec:iab:iabdpa:201816 is not listed on IDEAS
    6. repec:eee:enepol:v:111:y:2017:i:c:p:95-101 is not listed on IDEAS
    7. Andrés F. Barrientos & Alexander Bolton & Tom Balmat & Jerome P. Reiter & John M. de Figueiredo & Ashwin Machanavajjhala & Yan Chen & Charles Kneifel & Mark DeLong, 2017. "A Framework for Sharing Confidential Research Data, Applied to Investigating Differential Pay by Race in the U. S. Government," NBER Working Papers 23534, National Bureau of Economic Research, Inc.
    8. Satkartar K. Kinney & Jerome P. Reiter & Javier Miranda, 2014. "Improving The Synthetic Longitudinal Business Database," Working Papers 14-12, Center for Economic Studies, U.S. Census Bureau.
    9. Gedikoglu, Haluk & Parcell, Joseph L., 2013. "Implications of Survey Sampling Design for Missing Data Imputation," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149679, Agricultural and Applied Economics Association.
    10. Drechsler, Jörg & Reiter, Jerome P., 2011. "An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3232-3243, December.
    11. Klein Martin & Sinha Bimal, 2013. "Statistical Analysis of Noise-Multiplied Data Using Multiple Imputation," Journal of Official Statistics, Sciendo, vol. 29(3), pages 425-465, June.
    12. Drechsler, Jörg, 2011. "Methodenreport: Synthetische Scientific-Use-Files der Welle 2007 des IAB-Betriebspanels," FDZ Methodenreport 201101_de, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    13. repec:jss:jstsof:v:074:i11 is not listed on IDEAS
    14. Jerome P. Reiter, 2009. "Using Multiple Imputation to Integrate and Disseminate Confidential Microdata," International Statistical Review, International Statistical Institute, vol. 77(2), pages 179-195, August.
    15. Morehart, Mitch & Milkove, Dan & Xu, Yang, 2014. "Multivariate Farm Debt Imputation in the Agricultural Resource Management Survey (ARMS)," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169401, Agricultural and Applied Economics Association.
    16. Rashid, S. & Mitra, R. & Steele, R.J., 2015. "Using mixtures of t densities to make inferences in the presence of missing data with a small number of multiply imputed data sets," Computational Statistics & Data Analysis, Elsevier, vol. 92(C), pages 84-96.
    17. Yulia V. Marchenko & Jerome P. Reiter, 2009. "Improved degrees of freedom for multivariate significance tests obtained from multiply imputed, small-sample data," Stata Journal, StataCorp LP, vol. 9(3), pages 388-397, September.

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