ALikert 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).
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
Likert scaling is a bipolar scaling method, measuring either positive or negative response to a statement. Sometimes Likert scales are used in a forced choice method where 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).
After the questionnaire is completed, each item may be analyzed separately or 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 analyzed using non-parametric tests, such as the Mann-Whitney test, the Wilcoxon signed-rank test, and the Kruskal-Wallis test.[1]
When responses to several Likert items are summed, they may be treated as interval data measuring a latent variable. If the summed responses are normally distributed, parametric statistical tests such as the analysis of variance can be applied.
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.
The five response categories represent an ordinal level of measurement. The categories represent an inherent order (more to less, stronger to weaker, bigger to smaller), but the numbers assigned to the categories do not indicate the magnitude of difference between the categories in the way that an interval or ratio scale would.
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.
