Likert scale
1800s: Martineau · Tocqueville · Marx · Spencer · Le Bon · Ward · Pareto · Tönnies · Veblen · Simmel · Durkheim · Addams · Mead · Weber · Du Bois · Mannheim · Elias A Likert scale (/ˈlɪkərt/ LIK-ərt,[1][note 1]) is a psychometric scale named after its inventor, American social psychologist Rensis Likert,[2] which is commonly used in research questionnaires.
[6] A scale can be created as the simple sum or average of questionnaire responses over the set of individual items (questions).
A 1987 study found negligible differences between the use of "undecided" and "neutral" as the middle option in a five-point Likert scale.
This disagreement can be traced back, in many respects, to the extent to which Likert items are interpreted as being ordinal data.
The value assigned to a Likert item has no objective numerical basis, either in terms of measure theory or scale (from which a distance metric can be determined).
The value assigned to each Likert item is simply determined by the researcher designing the survey, who makes the decision based on a desired level of detail.
[14] Further, this progressive structure of the scale is such that each successive Likert item is treated as indicating a 'better' response than the preceding value.
The second, and possibly more important point, is whether the "distance" between each successive item category is equivalent, which is inferred traditionally.
A good Likert scale, as above, will present a symmetry of categories about a midpoint with clearly defined linguistic qualifiers.
This can be beneficial since, if it was treated just as an ordinal scale, then some valuable information could be lost if the 'distance' between Likert items were not available for consideration.
If interval nature is assumed for a comparison of two groups, the paired samples t-test is not inappropriate.
[citation needed] If the summed responses fulfill these assumptions, parametric statistical tests such as the analysis of variance can be applied.
In addition, the polytomous Rasch model permits testing of the hypothesis that the statements reflect increasing levels of an attitude or trait, as intended.
The subject of plotting Likert (and other) rating data is discussed at length in two papers by Robbins and Heiberger.
[18] In the first they recommend the use of what they call diverging stacked bar charts and compare them to other plotting styles.
Another paper [20]also provided Python code to create a clustered diverging stacked bar chart of 5-point Likert scale responses.
So these items and other equal-appearing scales in questionnaires are robust to violations of the equal distance assumption many researchers believe are required for parametric statistical procedures and tests.
