Survey Item Nonresponse and its Treatment

  • Susanne Rässler
  • Regina T. Riphahn


One of the most salient data problems empirical researchers face is the lack of informative responses in survey data. This contribution briefly surveys the literature on item nonresponse behavior and its determinants before it describes four approaches to address item nonresponse problems: Casewise deletion of observations, weighting, imputation, and model-based procedures. We describe the basic approaches, their strengths and weaknesses and illustrate some of their effects using a simulation study. The paper concludes with some recommendations for the applied researcher.


Multiple Imputation Complete Case Analysis Single Imputation Miss Data Mechanism Multiple Imputation Procedure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin · Heidelberg 2006

Authors and Affiliations

  • Susanne Rässler
    • 1
  • Regina T. Riphahn
    • 2
  1. 1.Kompetenzzentrum für Empirische MethodenIAB Institut für Arbeitsmarkt- und BerufsforschungDeutschland
  2. 2.Lehrstuhl für Statistik und empirische WirtschaftsforschungUniversität Erlangen-NürnbergDeutschland

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