The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Effect of the Number of Response Categories on the Reliability and Validity of Rating Scales
Open accessAbstract
The Likert-type format is one of the most widely used in all types of scales in the field of social sciences. Nevertheless, there is no definitive agreement on the number of response categories that optimizes the psychometric properties of the scales. The aim of the present work is to determine in a systematic fashion the number of response alternatives that maximizes the fundamental psychometric properties of a scale: reliability and validity. The study is carried out with data simulated using the Monte Carlo method. We simulate responses to 30 items with correlations between them ranging from 0.2 to 0.9. We also manipulate sample size, analyzing four different sizes: 50, 100, 200, and 500 cases. The number of response options employed ranges from two to nine. The results show that as the number of response alternatives increases, both reliability and validity improve. The optimum number of alternatives is between four and seven. With fewer than four alternatives the reliability and validity decrease, and from seven alternatives onwards psychometric properties of the scale scarcely increase further. Some applied implications of the results are discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
From dissertation abstracts international
(1974) · ACM SIGGRAPH Computer Graphics · doi:10.1145/988616.988619 · Cited by 12,099
On the practice of dichotomization of quantitative variables.
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.19 · Cited by 3,538
Humphreys, L. G., & Torgerson, W. (1965) · American Psychologist · doi:10.1037/h0021468 · Cited by 1,594
(2021) · Archives of Psychology · doi:10.31296/aop · Cited by 492
Effect of the number of scale points on reliability: A Monte Carlo approach.
Lissitz, R. W., & Green, S. B. (1975) · Journal of Applied Psychology · doi:10.1037/h0076268 · Cited by 488
DeVellis, R. F. (2006) · Medical Care · doi:10.1097/01.mlr.0000245426.10853.30 · Cited by 459
Weng, L.-J. (2004) · Educational and Psychological Measurement · doi:10.1177/0013164404268674 · Cited by 410
Bernstein, I. H., & Teng, G. (1989) · Psychological Bulletin · doi:10.1037//0033-2909.105.3.467 · Cited by 321
Babakus, E., Ferguson, C. E., & Jöreskog, K. G. (1987) · Journal of Marketing Research · doi:10.1177/002224378702400209 · Cited by 304
Cicchetti, D. V., Shoinralter, D., & Tyrer, P. J. (1985) · Applied Psychological Measurement · doi:10.1177/014662168500900103 · Cited by 291
Cited by
Weijters, B., Cabooter, E., & Schillewaert, N. (2010) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2010.02.004 · Cited by 801
Delphi methodology in health research: how to do it?
Trevelyan, E. G., & Robinson, P. N. (2015) · European Journal of Integrative Medicine · doi:10.1016/j.eujim.2015.07.002 · Cited by 745
Simms, L. J., Zelazny, K., Williams, T. F., & Bernstein, L. (2019) · Psychological Assessment · doi:10.1037/pas0000648 · Cited by 441
Diseño del formato de escalas tipo Likert: un estado de la cuestión
Matas, A. (2018) · Revista Electrónica de Investigación Educativa · doi:10.24320/redie.2018.20.1.1347 · Cited by 429
Green, S. B., & Yang, Y. (2009) · Psychometrika · doi:10.1007/s11336-008-9099-3 · Cited by 428
Metadata
- Authors
- Lozano, L. M., García-Cueto, E., & Muñiz, J.
- Venue
- Methodology
- Publisher
- Hogrefe Publishing Group
- Published
- 2008-01
- Volume
- 4
- Issue
- 2
- Pages
- 73-79
- ISSN
- 1614-1881 (ISSN-L)
- 1614-2241
- OpenAlex
- W2139953723
- Cited by
- 843
- References
- 34
- FWCI
- 23.06
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Effect of the Number of Response Categories on the Reliability and Validity of Rating Scales. https://app.cochat.ai/papers/10.1027/1614-2241.4.2.73
- The paper
- Lozano, L. M., García-Cueto, E., & Muñiz, J. (2008). Effect of the Number of Response Categories on the Reliability and Validity of Rating Scales. Methodology. https://doi.org/10.1027/1614-2241.4.2.73
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
