How many response categories are sufficient for Likert type scales? An empirical study based on the Item Response Theory

Yıl 2022, , 534 - 547, 26.06.2022

Eren Can Aybek Cetin Toraman

https://doi.org/10.21449/ijate.1132931

Cited By: 14

Öz

The current study investigates the optimum number of response categories for the Likert type of scales under the item response theory (IRT). The data was collected from university students attend to mainly the faculty of medicine and the faculty of education. A form of the “Social Gender Equity Scale” developed by Gozutok et al. (2017) was prepared, which had 3, 5 and 7-point response categories. The graded response model (GRM) was used for item calibrations. The results of the study have revealed that using a 5-point response option provides advantages over using a 3-point response category in terms of reliability and test information perspective in the scale development process. The-5 point scale also provides easier responding process for the respondents while it does not pose a major disadvantage compared to a 7-point response category in the terms of reliability. Therefore, based on the findings of the study, researchers are recommended to use a 5-point response category in their scale development process.

Anahtar Kelimeler

Likert-type scale, Response categories, Item response theory

Kaynakça

• Adelson, J.L., & McCoach, D.B. (2010). Measuring the mathematical attitudes of elementary students: The effects of a 4-point or 5-point Likert-Type scale. Educational and Psychological Measurement, 70(5) 796-807. https://doi.org/10.1177/0013164410366694
• Aiken, L.R. (1983). Number of response categories and statistics on a teacher rating scale. Educational and Psychological Measurement, 43, 397-401.
• Anastasi, A., & Urbina, S. (1997). Psychological testing. The USA: Prentice-Hall International, Inc.
• Bora, B. (2013). Pazarlama araştırmalarında kullanılan likert türü ölçeklerin uygulanabilirliğinin incelenmesi [A Study on The Applicability of The Likert Type Scales in Marketing] [Unpublished doctoral dissertation]. Sakarya University.
• Chalmers, R.P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1 29. https://doi.org/10.18637/jss.v048.i06
• Champney, H., & Marshall, H. (1939). Optimal refinement of the rating scale. Journal of Applied Psychology, 23, 323-331.
• Chang, L. (1994). A psychometric evaluation of 4-point and 6-point Likert-type scales in relation to reliability and validity. Applied Psychological Measurement, 18(3), 205-215. https://doi.org/10.1177/014662169401800302
• Dawes, J. (2008). Do data characteristics change according to the number of scale points used? An experiment using 5-point, 7-point and 10-point scales. International Journal of Market Research, 50(1), 61-104. https://doi.org/10.1177/147078530805000106
• DeVellis, R.F. (2003). Scale development, theory and applications. SAGE Publications.
• Dunn-Rankin, P., Knezek, G.A., Wallace, S., & Zhang, S. (2004). Scaling methods. Lawrence Erlbaum Associates, Inc.
• Gozutok, F.D., Toraman, C. ve Acar Erdol, T. (2017). Toplumsal cinsiyet eşitliği ölçeğinin (TCEÖ) geliştirilmesi [Development of gender equality scale]. İlköğretim Online Dergisi (Elementary Education Online), 16(3), 1036 1048. http://dx.doi.org/10.17051/ilkonline.2017.330240
• Jamieson, S. (2004). Likert Scales: How to (Ab)use them. Medical Education, 38, 1217‐1218.
• Joshi, A., Kale, S., Chandel, S., & Pal, D.K. (2015). Likert scale: Explored and explained. British Journal of Applied Science & Technology (BJAST), 7(4), 396-403. https://doi.org/10.9734/BJAST/2015/14975
• Leung, S.O. (2011). A comparison of psychometric properties and normality in 4-, 5-, 6-, and 11-point Likert Scales. Journal of Social Service Research, 37, 412-421. https://doi.org/10.1080/01488376.2011.580697
• Lord, F.M. (1954). Chapter II: Scaling. Review of Educational Research, 24(5), 375-392. https://doi.org/10.3102/00346543024005375
• Norman, G. (2010). Likert scales, levels of measurement and the “laws” of statistics. Adv in Health Sci Educ 15, 625-632. https://doi.org/10.1007/s10459-010-9222-y
• Nunnally, J.C., & Bernstein, I. H. (1994). Psychometric theory. McGraw-Hill, Inc.
• Preston, C.C., & Colman, A. M. (2000). Optimal number of response categories in rating scales: reliability, validity, discriminating power, and respondent preferences. Acta Psychologica 104, 1-15. https://doi.org/10.1016/s0001-6918(99)00050-5
• Price, L.R. (2017). Psychometric methods, theory into practice. New York: The Guilford Press
• R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
• Revelle, W. (2021) psych: Procedures for Personality and Psychological Research, Northwestern University, Evanston, Illinois, USA, https://CRAN.R project.org/package=psych version=2.1.6.
• Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103, 677-680.
• Thomas, H. (1982). IQ interval scales, and normal distributions. Psychological Bulletin, 91, 198-202.
• Toraman, C. & Ozen, F. (2019). An investigation of the effectiveness of the gender equality course with a specific focus on faculties of education. Educational Policy Analysis and Strategic Research, 14(2), 6-28. https://doi.org/10.29329/epasr.2019.201.1
• Torgerson, W.S. (1958). Theory and methods of scaling. New York: John Willey & Sons, Inc.
• Wong, C.-S., Chuen, K.-C., & Fung, M.-Y. (1993). Differences between odd and even number of response scales: Some empirical evidence. Chinese Journal of Psychology, 35, 75-86.
• Wu, H., & Leung, S.O. (2017) Can Likert Scales be treated as interval scales? A simulation study. Journal of Social Service Research, 43(4), 527 532. https://doi.org/10.1080/01488376.2017.1329775