Detecting careless respondents in web-based questionnaires: Which method to use?

Abstract

High data quality is an important prerequisite for sound empirical research. Meade and Craig (2012) and Huang, Curran, Keeney, Poposki, and DeShon (2012) discussed methods to detect unmotivated or careless respondents in large web-based questionnaires. We first discuss these methods and present multi-test extensions of person-fit statistics as alternatives. Second, we applied these methods to data collected through a web-based questionnaire, in which some respondents received instructions to respond quickly which can result in more careless responding. In addition, we conducted a simulation study. We compared sensitivity and specificity of different methods and concluded that multi-test extensions of person-fit statistics are a good alternative as compared to other methods, although the sensitivity to detect careless respondents using empirical data was lower than using simulated data.

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