IDEAS home Printed from https://ideas.repec.org/p/zbw/faucse/652004.html
   My bibliography  Save this paper

Multiple imputation for unit-nonresponse versus weighting including a comparison with a nonresponse follow-up study

Author

Listed:
  • Rässler, Susanne
  • Schnell, Rainer

Abstract

The results of a national fear of crime survey are compared with results following the use of different nonresponse correction procedures. We compared naive estimates, weighted estimates, estimates after a thorough nonresponse follow-up and estimates after multiple imputation. A strong similarity between the MI and the follow-up-estimates was found. This suggests, that if the assumptions of MAR hold, carefully selected and collected additional data applied in a MI could yield similar estimates to a nonresponse follow-up at a much lower price and respondent burden.

Suggested Citation

  • Rässler, Susanne & Schnell, Rainer, 2004. "Multiple imputation for unit-nonresponse versus weighting including a comparison with a nonresponse follow-up study," Discussion Papers 65/2004, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    • Handle: RePEc:zbw:faucse:652004
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/29622/1/614049911.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Donald B. Rubin, 2003. "Nested multiple imputation of NMES via partially incompatible MCMC," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(1), pages 3-18, February.
    2. Rubin, Donald B, 1986. "Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 87-94, January.
    3. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    4. Rässler, Susanne & Koller, Florian & Mäenpää, Christine, 2002. "A split questionnaire survey design applied to German media and consumer surveys," Discussion Papers 42b/2002, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joost Ginkel & Pieter Kroonenberg, 2014. "Using Generalized Procrustes Analysis for Multiple Imputation in Principal Component Analysis," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 242-269, July.
    2. Brownstone, David, 1997. "Multiple Imputation Methodology for Missing Data, Non-Random Response, and Panel Attrition," University of California Transportation Center, Working Papers qt2zd6w6hh, University of California Transportation Center.
    3. Westermeier, Christian & Grabka, Markus M., 2016. "Longitudinal Wealth Data and Multiple Imputation: An Evaluation Study," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(3), pages 237-252.
    4. Arif Mamun & David Wittenburg & Noelle Denny-Brown & Michael Levere & David Mann & Rebecca Coughlin & Sarah Croake & Heather Gordon & Denise Hoffman & Rachel Holzwart & Rosalind Keith & Brittany McGil, "undated". "Promoting Opportunity Demonstration: Interim Evaluation Report," Mathematica Policy Research Reports caa99d38a8b14f968ea3438e5, Mathematica Policy Research.
    5. Gowri Gopalakrishna & Gerben ter Riet & Gerko Vink & Ineke Stoop & Jelte M Wicherts & Lex M Bouter, 2022. "Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in The Netherlands," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-16, February.
    6. Fumagalli, Laura & Sala, Emanuela, 2011. "The total survey error paradigm and pre-election polls: the case of the 2006 Italian general elections," ISER Working Paper Series 2011-29, Institute for Social and Economic Research.
    7. Baltussen, Guido & Swinkels, Laurens & Van Vliet, Pim, 2021. "Global factor premiums," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1128-1154.
    8. Sean Mc Auliffe & Georg U. Thunecke & Georg Wamser, 2023. "The Tax-Elasticity of Tangible Fixed Assets: Evidence from Novel Corporate Tax Data," CESifo Working Paper Series 10628, CESifo.
    9. Leonie C. Steckermeier & Jan Delhey, 2019. "Better for Everyone? Egalitarian Culture and Social Wellbeing in Europe," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 1075-1108, June.
    10. Saeideh Kamgar & Florian Meinfelder & Ralf Münnich & Hamidreza Navvabpour, 2020. "Estimation within the new integrated system of household surveys in Germany," Statistical Papers, Springer, vol. 61(5), pages 2091-2117, October.
    11. Filippo Battistoni & Marco Martinez, 2022. "Rome and the Polis: Tradition and Change in the Financial Accounts of Tauromenion, 1st Century B.C," Annals of the Fondazione Luigi Einaudi. An Interdisciplinary Journal of Economics, History and Political Science, Fondazione Luigi Einaudi, Torino (Italy), vol. 56(1), pages 149-176, June.
    12. 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, vol. 95(4), pages 351-373, December.
    13. Roderick J. A. Little & Donald B. Rubin, 1989. "The Analysis of Social Science Data with Missing Values," Sociological Methods & Research, , vol. 18(2-3), pages 292-326, November.
    14. Jana Emmenegger & Ralf Münnich & Jannik Schaller, 2022. "Evaluating Data Fusion Methods to Improve Income Modelling," Research Papers in Economics 2022-03, University of Trier, Department of Economics.
    15. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
    16. Chenyang Gu & Roee Gutman, 2017. "Combining item response theory with multiple imputation to equate health assessment questionnaires," Biometrics, The International Biometric Society, vol. 73(3), pages 990-998, September.
    17. Rasner, Anika & Frick, Joachim R. & Grabka, Markus M., 2013. "Statistical Matching of Administrative and Survey Data: An Application to Wealth Inequality Analysis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 42(2), pages 192-224.
    18. Chia-Ning Wang & Roderick Little & Bin Nan & Siobán D. Harlow, 2011. "A Hot-Deck Multiple Imputation Procedure for Gaps in Longitudinal Recurrent Event Histories," Biometrics, The International Biometric Society, vol. 67(4), pages 1573-1582, December.
    19. Schenker, Nathaniel & Taylor, Jeremy M. G., 1996. "Partially parametric techniques for multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 425-446, August.
    20. Matthias von Davier & Youngmi Cho & Tianshu Pan, 2019. "Effects of Discontinue Rules on Psychometric Properties of Test Scores," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 147-163, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:faucse:652004. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/vierlde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.