Guttman Scale

Guttman Scale definition

A Guttman scale (also known as cumulative scaling or scalogram analysis) is an ordinal scale type where statements are arranged in a hierarchical order so that someone who agrees with one item will also agree with lower-order, easier, less extreme items. These statements should reflect an increasing intensity of attitude and form a continuum that is accepted by the respondents.  The point at which the respondent disagrees with a statement reflects the respondent’s scale position.

A Guttman scale presents a number of items to which the person is requested to agree or not agree. This is typically done in a 'Yes/No' dichotomous format. It is also possible to use a Likert scale, although this is less commonly used.

Guttman scales are very commonly used in political science, anthropology, public opinion, research, and psychology.

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Guttman scale examples

The ideal Guttman scale is such that if the respondent disagrees, for example, with statement 4 (having agreed with statements 1 to 3) then the respondent will disagree with statement 5 and higher as these represent more extreme expressions of the attitude being investigated.

For example, a series of items on attitude could be

  1. "I am willing to be near a cat"
  2. "I am willing to have a cat"
  3. "I love to have a cat"
  4. "I am willing to touch a cat"

Or a series of items on difficulty:

  1. counting from 1 to 50
  2. solving addition problems
  3. solving subtraction problems
  4. solving multiplication problems
  5. solving division problems

guttman scale example

Guttman scale advantages

  • It can be used to answer many questions in a short amount of space and/or time.
  • It is intuitively appealing to most people.
  • It provides ranked data.
  • Reproducibility
  • More one-dimensional than Likert scaling

Guttman scale disadvantages

  • The rank order of the statements may not be interpreted in the same way by the researcher, the subject, or by independent judges.
  • Difficult to construct
  • Scalogram analysis may be too restrictive, only a narrow universe of content can be used
  • Cornell technique questionable
  • Results no better than summated Likert scales

Other scale types

  • Survey scales - a scale is an ordered series of response options, presented verbally or numerically from which the respondents select to indicate their level of feeling about the measured attribute. 
  • Likert scale - Questions utilizing a Likert scale generally present the respondent with a statement and asks for his/her level of agreement with the statement by selecting a point on the scale. These points have often verbal statements or numbers attached to them. The scale should be balanced between positive and negative agreement options.
  • Verbal scale - a verbal scale also referred to as a “word statement” or “scale expression”, is where the response options are presented to the respondent using words, whether spoken or written. 
  • Continuous scale - On a continuous scale, respondents rate the objects by placing a mark at the appropriate position on a line that runs from one extreme of the variable to the other. The form of the continuous scale may vary considerably. 
  • Comparative scale - Comparative scales involve the direct comparison of stimulus objects. Most often, the respondent is asked to compare one brand, product or feature against another. Comparative scale data must be interpreted in relative terms and have only ordinal or rank order properties. 
  • Discrete scale - Discrete data, like counts, are numeric data that have a finite number of possible values and can only be whole numbers. Discrete data arise from observations that can only take certain numerical values. Fractions are meaningless. In some situations, mathematical functions or calculations are not possible either. 
  • Forced choice scale - A forced-choice scale (also known as an ipsative scale) is a rating scale that does not allow for an Undecided, Neutral, Doesn't know, or No opinion response. 

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Vincent is the author of this solution article.

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