A review of techniques for treating missing data in OM survey research

Nikos Tsikriktsis

311 citations0/0 files storedJournal of Operations Management

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Survey Methodology and Nonresponse Statistical Methods and Bayesian Inference Survey Sampling and Estimation Techniques

Abstract

Abstract The treatment of missing data has been overlooked by the OM literature, while other fields such as marketing, organizational behavior, economics, statistics and psychometrics have paid more attention to the issue. A review of 103 survey‐based articles published in the Journal of Operations Management between 1993 and 2001 shows that listwise deletion, which is often the least accurate technique of dealing with missing data, is heavily utilized by OM researchers. The paper also discusses the research implications of missing data, types of missing data and concludes with recommendations on which techniques should be used under different circumstances in order to improve the treatment of missing data in OM survey research.

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References

1998Principles and Practice of Structural Equation Modeling 1990Empirical research methods in operations management 1998Missing Data in Likert Ratings: A Comparison of Replacement Methods 2002Techniques for improving response rates in OM survey research

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