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How do MIS researchers handle missing data in survey-based research: A content analysis approach

Author

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  • Karanja, Erastus
  • Zaveri, Jigish
  • Ahmed, Ashraf

Abstract

Missing data is a common occurrence in survey-based research studies. However, the issue of missing data in Management Information Systems (MIS) literature has been overlooked, unlike the case in other disciplines such as Psychology, Marketing, Statistics, and Operations Management. The aim of this paper is to narrow this gap in the MIS field by investigating how MIS researchers address issues of missing data. This paper briefly outlines the causes of missing data in survey-based research as well as the common remedial techniques available to researchers. The paper also reviews how the common statistical software programs namely PASW (SPSS), SAS, LISREL, AMOS, EQS, and PLS handle missing data. It summarizes the common missing data remedial techniques and procedures and outlines how the presence of missing data affect sample size, statistical power, parameter estimates, ability to cope with different missing data patterns, and ease of implementation. Following that is a review of 749 survey-based research articles published between 1990 and 2010 in nine mainstream MIS Journals. The results reveal that researchers rarely report, explicitly, the presence or treatment of missing data and that when they do – they tend to use the least accurate techniques of listwise and pairwise deletion. The research concludes with recommendations that include a call for editorial policies that encourage the reporting of missing data, the reporting of the chosen missing data treatment techniques as well as the justifications for the techniques adopted by the researchers. The authors assert, based on the research, that following these recommendations will affect the rigor and quality of MIS survey-based research.

Suggested Citation

  • Karanja, Erastus & Zaveri, Jigish & Ahmed, Ashraf, 2013. "How do MIS researchers handle missing data in survey-based research: A content analysis approach," International Journal of Information Management, Elsevier, vol. 33(5), pages 734-751.
    • Handle: RePEc:eee:ininma:v:33:y:2013:i:5:p:734-751
    DOI: 10.1016/j.ijinfomgt.2013.05.002
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    References listed on IDEAS

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