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Much Ado About Nothing: A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models

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  • Horton, Nicholas J.
  • Kleinman, Ken P.

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Bibliographic Info

Article provided by American Statistical Association in its journal The American Statistician.

Volume (Year): 61 (2007)
Issue (Month): (February)
Pages: 79-90

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Handle: RePEc:bes:amstat:v:61:y:2007:m:february:p:79-90

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Cited by:
  1. David Madden, 2012. "The Relationship Between Low Birthweight and Socioeconomic Status in Ireland," Working Papers 201214, School Of Economics, University College Dublin.
  2. Dardanoni, Valentino & Modica, Salvatore & Peracchi, Franco, 2011. "Regression with imputed covariates: A generalized missing-indicator approach," Journal of Econometrics, Elsevier, vol. 162(2), pages 362-368, June.
  3. Juned Siddique & Ofer Harel, . "MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors," Journal of Statistical Software, American Statistical Association, vol. 29(i09).
  4. Cain Polidano & Ha Vu, 2012. "Labour Market Impacts from Disability Onset," Melbourne Institute Working Paper Series wp2012n22, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  5. Fulvio Castellacci & José Miguel Natera, 2011. "A new panel dataset for cross-country analyses of national systems, growth and development (CANA)," Working Papers del Instituto Complutense de Estudios Internacionales 05-11, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
  6. Gedikoglu, Haluk & Parcell, Joseph, 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.
  7. Valentino Dardanoni & Giuseppe De Luca & Salvatore Modica & Franco Peracchi, 2011. "A Generalized Missing-Indicator Approach to Regression with Imputed Covariates," EIEF Working Papers Series 1111, Einaudi Institute for Economics and Finance (EIEF), revised May 2011.
  8. Hapfelmeier, A. & Hothorn, T. & Ulm, K., 2012. "Recursive partitioning on incomplete data using surrogate decisions and multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1552-1565.
  9. Consentino, Fabrizio & Claeskens, Gerda, 2010. "Order selection tests with multiply imputed data," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2284-2295, October.
  10. Schomaker, Michael & Heumann, Christian, 2014. "Model selection and model averaging after multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 758-770.
  11. Kristian Kleinke & Mark Stemmler & Jost Reinecke & Friedrich Lösel, 2011. "Efficient ways to impute incomplete panel data," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 351-373, December.

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