Choosing the Number of Categories in Agree–Disagree Scales
By Melanie Revilla, Willem E. Saris, J. Krosnick. 2014
555 citations recorded by the source corpus.
Although agree–disagree (AD) rating scales suffer from acquiescence response bias, entail enhanced cognitive burden, and yield data of lower quality, these scales remain popular with researchers due to practical considerations (e.g., ease of item preparation, speed of administration, and reduced administration costs). This article shows that if researchers want to use AD scales, they should offer 5 answer categories rather than 7 or 11, because the latter yield data of lower quality. This is shown using data from four multitrait-multimethod experiments implemented in the third round of the European Social Survey. The quality of items with different rating scale lengths were computed and compared.
Subfields: Applied Psychology, Management Science and Operations Research, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/c8bf32767ecdad715704d2dd68af945e5edddefa
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In Management Science and Operations Research
In Sociology and Political Science
Citations in the corpus
- The comparison of estimation methods on the parameter estimates and fit indices in SEM model under 7-point Likert scale (2017, background): “Therefore, issues are not discussed which pertain to the selection of the optimal number of categories within the scale, as these issues have been profoundly described in the literature (Alwin 1992; Dawes 2008; Revilla, Saris, and Krosnick 2014; Tarka 2016).”
- Using Likert Type Data in Social Science Research: Confusion, Issues and Challenges (2016, background): “49 Rinker, T. (2014). Treatment of Likert data.”
- How Does Sustainable Leadership Influence Sustainable Performance? Empirical Evidence From Selected ASEAN Countries (2020, background): “But possible acquiescence bias responses linked to agree–disagree (AD) Likert-type scales result into enhanced cognitive burden and low-quality data (Revilla et al., 2014).”