Effect of the Number of Response Categories on the Reliability and Validity of Rating Scales

Abstract

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.