A Catalog of Biases in Questionnaires

By B. Choi, A. Pak. 2004

885 citations recorded by the source corpus.

Bias in questionnaires is an important issue in public health research. To collect the most accurate data from respondents, investigators must understand and be able to prevent or at least minimize bias in the design of their questionnaires. This paper identifies and categorizes 48 types of bias in questionnaires based on a review of the literature and offers an example of each type. The types are categorized according to three main sources of bias: the way a question is designed, the way the questionnaire as a whole is designed, and how the questionnaire is administered. This paper is intended to help investigators in public health understand the mechanism and dynamics of problems in questionnaire design and to provide a checklist for identifying potential bias in a questionnaire before it is administered.

Subfields: Statistics and Probability, Social Sciences & Humanities

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In Statistics and Probability

1. Elizabeth Clark
2. Eric Kow
3. Anya Belz
4. Sebastian Gehrmann

Citations in the corpus

• Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text (2022, background): “Choi and Pak (2005) provide a longer catalogue covering 48 of these biases.”
• Comparing Rating Scales and Preference Judgements in Language Evaluation (2010, background): “…scales, e.g. what is known as ‘end-aversion’ tendency where certain individuals tend to stay away from the extreme ends of scales; other examples are positive skew and acquiescence bias, where individuals make disproportionately many positive or agreeing judgements; see e.g. Choi and Pak, (2005).”
• Generating Referring Expressions in Context: The GREC Task Evaluation Challenges (2010, neutral): “[8]).”