Likert scale

A Likert scale (pronounced 'lick-urt') is a type of psychometric response scale often used in questionnaires, and is the most widely used scale in survey research. When responding to a Likert questionnaire item, respondents specify their level of agreement to a statement. The scale is named after Rensis Likert, who published a report describing its use (Likert, 1932).

Sample question presented using a five-point Likert Scale

A typical test item in a Likert scale is a statement. The respondent is asked to indicate his or her degree of agreement with the statement or any kind of subjective or objective evaluation of the statement. Traditionally a five-point scale is used, however many psychometricians advocate using a seven or nine point scale.

Ice cream is good for breakfast

1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree

Likert scaling is a bipolar scaling method, measuring either positive or negative response to a statement. Sometimes a four-point scale is used; this is a forced choice method since the middle option of "Neither agree nor disagree" is not available. Likert scales may be subject to distortion from several causes. Respondents may avoid using extreme response categories (central tendency bias); agree with statements as presented (acquiescence bias); or try to portray themselves or their organization in a more favorable light (social desirability bias).

Scoring and analysis

After the questionnaire is completed, each item may be analyzed separately or in some cases item responses may be summed to create a score for a group of items. Hence, Likert scales are often called summative scales.

Responses to a single Likert item are normally treated as ordinal data, because, especially when using only five levels, one cannot assume that respondents perceive the difference between adjacent levels as equidistant. When treated as ordinal data, Likert responses can be collated into bar charts, central tendency summarised by the median or the mode (but not the mean), dispersion summarised by the range across quartiles (but not the standard deviation), or analyzed using non-parametric tests, e.g. Chi-square test, Mann-Whitney test, Wilcoxon signed-rank test, or Kruskal-Wallis test.^[1]

Responses to several Likert questions may be summed, providing that all questions use the same Likert scale and that the scale is a defendable approximation to an interval scale, in which case they may be treated as interval data measuring a latent variable. If the summed responses fulfils these assumptions, parametric statistical tests such as the analysis of variance can be applied. These can be applied only when the components are more than 5.

Data from Likert scales are sometimes reduced to the nominal level by combining all agree and disagree responses into two categories of "accept" and "reject". The Chi-Square, Cochran Q, or McNemar-Test are common statistical procedures used after this transformation.

Consensus based assessment (CBA) can be used to create an objective standard for Likert scales in domains where no generally accepted standard or objective standard exists. Consensus based assessment (CBA) can be used to refine or even validate generally accepted standards.

Level of measurement

The five response categories represent an Interval level of measurement.

Rasch model

Likert scale data can, in principle, be used as a basis for obtaining interval level estimates on a continuum by applying the polytomous Rasch model, when data can be obtained that fit this model. In addition, the polytomous Rasch model permits testing of the hypothesis that the statements reflect increasing levels of an attitude or trait, as intended. For example, application of the model often indicates that the neutral category does not represent a level of attitude or trait between the disagree and agree categories.