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Survey item nonresponse and its treatment

Author

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  • Susanne Rässler

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  • Regina Riphahn

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Abstract

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Suggested Citation

  • Susanne Rässler & Regina Riphahn, 2006. "Survey item nonresponse and its treatment," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 217-232, March.
  • Handle: RePEc:spr:alstar:v:90:y:2006:i:1:p:217-232
    DOI: 10.1007/s10182-006-0231-3
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    File URL: http://hdl.handle.net/10.1007/s10182-006-0231-3
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    References listed on IDEAS

    as
    1. Regina Riphahn & Oliver Serfling, 2005. "Item non-response on income and wealth questions," Empirical Economics, Springer, vol. 30(2), pages 521-538, September.
    2. Joachim R. Frick & Markus M. Grabka, 2003. "Missing Income Data in the German SOEP: Incidence, Imputation and its Impact on the Income Distribution," Discussion Papers of DIW Berlin 376, DIW Berlin, German Institute for Economic Research.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Daniel Schunk, 2007. "A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey," MEA discussion paper series 07121, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    2. Ziegelmeyer, Michael, 2009. "Documentation of the logical imputation using the panel structure of the 2003-2008 German SAVE Survey," Papers 08-41, Sonderforschungsbreich 504.
    3. Thomas Y. Mathä & Alessandro Porpiglia & Michael Ziegelmeyer, 2012. "Income, Wealth and Consumption of Cross-Border Commuters to Luxembourg," BCL working papers 78, Central Bank of Luxembourg.
    4. Rässler, Susanne, 2006. "Der Einsatz von Missing Data Techniken in der Arbeitsmarktforschung des IAB," IAB-Forschungsbericht 200618, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Hübler, Olaf, 2013. "Methods in empirical economics - a selective review with applications," Hannover Economic Papers (HEP) dp-513, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Romina Boarini & Margherita Comola & Femke Keulenaer & Robert Manchin & Conal Smith, 2013. "Can Governments Boost People’s Sense of Well-Being? The Impact of Selected Labour Market and Health Policies on Life Satisfaction," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(1), pages 105-120, October.
    7. Uwe Jensen & Hermann Gartner & Susanne Rässler, 2010. "Estimating German overqualification with stochastic earnings frontiers," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(1), pages 33-51, March.
    8. Daniel Schunk, 2008. "A Markov chain Monte Carlo algorithm for multiple imputation in large surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 101-114, February.
    9. Frick, Joachim R. & Grabka, Markus M., 2007. "Item Non-Response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective," IZA Discussion Papers 3043, Institute for the Study of Labor (IZA).

    More about this item

    Keywords

    Item nonresponse; imputation; weighting; survey data. JEL C1; C81; C49;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

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