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Multiple Imputation in Practice: Comparison of Software Packages for Regression Models With Missing Variables

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  • Horton N. J.
  • Lipsitz S. R.

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  • Horton N. J. & Lipsitz S. R., 2001. "Multiple Imputation in Practice: Comparison of Software Packages for Regression Models With Missing Variables," The American Statistician, American Statistical Association, vol. 55, pages 244-254, August.
  • Handle: RePEc:bes:amstat:v:55:y:2001:m:august:p:244-254
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    Cited by:

    1. Janet MacNeil Vroomen & Iris Eekhout & Marcel G. Dijkgraaf & Hein van Hout & Sophia E. de Rooij & Martijn W. Heymans & Judith E. Bosmans, 2016. "Multiple imputation strategies for zero-inflated cost data in economic evaluations: which method works best?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 939-950, November.
    2. Ulrich Rendtel, 2006. "The 2005 Plenary Meeting on ‘‘Missing Data and Measurement Error’’," AStA Advances in Statistical Analysis, Springer;German Statistical Society, pages 493-499.
    3. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 52.
    4. Jing Dai & Stefan Sperlich & Walter Zucchini, 2016. "A Simple Method for Predicting Distributions by Means of Covariates with Examples from Poverty and Health Economics," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), pages 49-80.
    5. Patrick Royston & John B. Carlin & Ian R. White, 2009. "Multiple imputation of missing values: New features for mim," Stata Journal, StataCorp LP, pages 252-264.
    6. Hildegard Seidl & Matthias Hunger & Reiner Leidl & Christa Meisinger & Rupert Wende & Bernhard Kuch & Rolf Holle, 2015. "Cost-effectiveness of nurse-based case management versus usual care for elderly patients with myocardial infarction: results from the KORINNA study," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(6), pages 671-681, July.
    7. Paul Zhang, 2005. "Multiple imputation of missing data with ante-dependence covariance structure," Journal of Applied Statistics, Taylor & Francis Journals, pages 141-155.
    8. Andrew Briggs & Taane Clark & Jane Wolstenholme & Philip Clarke, 2003. "Missing.... presumed at random: cost-analysis of incomplete data," Health Economics, John Wiley & Sons, Ltd., vol. 12(5), pages 377-392.
    9. Ronald B. Mincy & Elia De la Cruz Toledo, 2014. "Unemployment and Child Support Compliance Through the Great Recession," Working Papers 14-01-ff, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Research on Child Wellbeing..
    10. Adnan Efendic & Tomasz Marek Mickiewicz & Anna Rebmann, 2013. "Growth Aspirations and Social Capital: Young Firms in a Post-Conflict Environment," UCL SSEES Economics and Business working paper series 122, UCL School of Slavonic and East European Studies (SSEES).
    11. Geronimi, J. & Saporta, G., 2017. "Variable selection for multiply-imputed data with penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, pages 103-114.
    12. Consentino, Fabrizio & Claeskens, Gerda, 2010. "Order selection tests with multiply imputed data," Computational Statistics & Data Analysis, Elsevier, pages 2284-2295.
    13. Gabriele Beissel Durrant, 2009. "Imputation Methods for Handling Item-Nonresponse in the Social Sciences: A Methodological Review," Working Papers id:2007, eSocialSciences.
    14. repec:eee:spacre:v:19:y:2016:i:1:p:142-153 is not listed on IDEAS
    15. Calzolari, Giorgio & Neri, Laura, 2002. "Imputation of continuous variables missing at random using the method of simulated scores," MPRA Paper 22986, University Library of Munich, Germany, revised 2002.
    16. David K. Blough & Scott Ramsey & Sean D. Sullivan & Roger Yusen, 2009. "The impact of using different imputation methods for missing quality of life scores on the estimation of the cost-effectiveness of lung-volume-reduction surgery," Health Economics, John Wiley & Sons, Ltd., vol. 18(1), pages 91-101.
    17. Ringle, Jay L. & Huefner, Jonathan C. & James, Sigrid & Pick, Robert & Thompson, Ronald W., 2012. "12-month follow-up outcomes for youth departing an integrated residential continuum of care," Children and Youth Services Review, Elsevier, pages 675-679.
    18. Jing Dai & Stefan Sperlich & Walter Zucchini, 2011. "Estimating and Predicting Household Expenditures and Income Distributions," MAGKS Papers on Economics 201147, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    19. Kristian Kleinke & Mark Stemmler & Jost Reinecke & Friedrich Lösel, 2011. "Efficient ways to impute incomplete panel data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, pages 351-373.
    20. Li, Daniel H. & Wang, Liqun, 2016. "A weighted simulation-based estimator for incomplete longitudinal data models," Statistics & Probability Letters, Elsevier, pages 16-22.
    21. Susanne Rässler & Regina Riphahn, 2006. "Survey item nonresponse and its treatment," AStA Advances in Statistical Analysis, Springer;German Statistical Society, pages 217-232.

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