Quality and Quantity

, Volume 35, Issue 2, pp 147–160

Reducing Missing Data in Surveys: An Overview of Methods

  • Edith D. de Leeuw
Article

DOI: 10.1023/A:1010395805406

Cite this article as:
de Leeuw, E.D. Quality & Quantity (2001) 35: 147. doi:10.1023/A:1010395805406

Abstract

Although item nonresponse can never be totally prevented, it can be considerably reduced, and thereby provide the researcher with not only more useable data, but also with helpful auxiliary information for a better imputation and adjustment. To achieve this an optimal data collection design is necessary. The optimization of the questionnaire and survey design are the main tools a researcher has to reduce the number of missing data in any such survey. In this contribution a concise typology of missing data patterns and their sources of origin are presented. Based on this typology, the mechanisms responsible for missing data are identified, followed by a discussion on how item nonresponse can be prevented.

item nonresponse causes of missingness cognitive pretest data collection mode ignorability question wording questionnaire development sensitive questions survey 

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Edith D. de Leeuw
    • 1
  1. 1.MethodikA AmsterdamCN AmsterdamThe Netherlands

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