Types of Scales/ measures

Scale.

A scale is a type of complex measure that is composed of several items that have a logical or empirical structure among them. That is, scales take advantage of differences in strength among the indicators of a variable. For example, when a question has the response choices of "always," "sometimes," "rarely," and "never," this is a scale because the answer choices are rank-ordered and have differences in intensity. Another example would be "strongly agree," "agree," "neither agree nor disagree," "disagree," "strongly disagree."

1.                  Likert Scale

Likert scales are one of the most commonly used scales in social science research. It is named after its creator, psychologist Rensis Likert. On a survey or questionnaire, the Likert scale typically has the following format:

1.                  Strongly agree

2.                  Agree

3.                  Neither agree nor disagree

4.                  Disagree

5.                  Strongly disagree

It should be noted that the individual questions that use this format are called Likert items while the Likert scale is a sum of several Likert items. To create the scale, each answer choice is assigned a score (say 0-4) and the answers for several Likert items (that measure the same concept) can be summed together for each individual to get an overall Likert score.

6.                  Thurstone Scale

The Thurstone scale, created by Louis Thurstone, is intended to develop a format for generating groups of indicators of a variable that have an empirical structure among them. For example, if you were studying discrimination, you would put together a list of items (we’ll use 10 items in this example) and then ask respondents to assign scores of 1 to 10 to each item. In essence, they are ranking the items in order of which is the weakest indicator of discrimination all the way to which is the strongest indicator. Once the respondents have scored the items, the researcher examines the scores assigned to each item by all the respondents to determine which items the respondents agreed upon the most. If the scale items were adequately developed and scored, the economy and effectiveness of data reduction present in the Bogardus social distance scale would appear.

Thurstone developed his method of equal appearing intervals on the concept that, even though people could not assign quantitative measurements to their own attitudes, they could tell the difference between the attitude represented by two different statements and could identify that were approximately halfway between the two.

 The procedure is as follows:

1) Collect a large number of statements (perhaps as many as several hundred) related to the attitude in question.
2) Have a number of judges (perhaps 20 or more) sort the statements independently into 11 piles that vary from the most unfavorable statements in pile one, to neutral statements in pile 6, to the most favorable statements in pile 11.
3) Study the frequency distribution of ratings for each statement and eliminate those statements that different judges have given widely scattered ratings that are in a number of different piles.
4) Determine the scale value of each of the remaining statements – that is the number of the pile in which the median of the distribution falls.
5) Select one or two statements from each of the 11 piles for the final scale. Those statements with the narrowest range of ratings are preferred as the most reliable. List the selected statements in random order to form the final scale.

The following statements are taken in order, one from each of the 11 positions, from a scale to measure attitude toward television commercials:

1) All TV commercials should be prohibited by law.
2) Watching TV commercials is a complete waste of time.
3) Most TV commercials are pretty bad.
4) TV commercials are monotonous
5) TV commercials do not interfere too much with enjoying TV.
6) I have no feeling one way or the other about most TV commercials
7) I like TV commercials at times
8) Most TV commercials are fairly interesting
9) I like to buy products advertised on TV whenever possible.
10) Most TV commercials help people select the best products available
11) TV commercials are more fun to watch than the regular programs.

Respondents whose attitudes are to be scaled are given the list of statements and asked to indicate agreement or disagreement with each statement. Presumably each respondent will agree with only one statement or with a few statements that are from immediately adjacent scale positions. For example, a respondent might agree with statements the scale values of which were 8, 9, and 10. Such an agreement in the above list would be interpreted as representing a favorable attitude toward television commercials. Respondents’ scores are computed as the median of the item numbers with which they agree. If respondents agreed with statements 1, 4, 7 and 11, it would be interpreted to indicate they did not have organized attitudes on the topic. If the scale has been properly prepared, few respondents should show such a varied group of attitudes.

7.                  Semantic Differential Scale

The semantic differential scale asks respondents of a questionnaire to choose between two opposite positions using qualifiers to bridge the gap between them. Let’s look at an example. Suppose you wanted to get respondents’ opinions about a new comedy television show. You must first decide what dimensions you wish to measure and then find two opposite terms that represent those dimensions. For example, "enjoyable" and “unenjoyable," "funny" and "not funny," "relatable" and "not relatable." You would then create a rating sheet for each respondent to indicate how they feel about the television show in each dimension. Your questionnaire would look something like this:

_1.                    Very Much Somewhat Neither Somewhat Very Much

_2.                    Enjoyable X Unenjoyable

_3.                    Funny X Not Funny

_4.                    Relatable X Unrelatable

Some more that a unique sort of attitude scale that is especially useful for classroom research is the semantic differential .It allows a researcher to measure a subject’s attitude toward a particular concept. Subjects are presented with a continuum of several pairs of adjectives (good-bad, cold-hot, priceless-worthless, and so on) and asked to place a check mark between each pair to indicate their attitudes.

Example……

Instructions: Listed below are several pairs of adjectives. Place a check mark (_) on the line between each pair to indicate how you feel.

Example: Hockey: Exciting: _____:_____:_____:_____:_____:_____:_____:_____:

dull if you feel that hockey is very exciting, you would place a check mark in the first space next to the word exciting. If you feel that hockey is very dull, you would place a check mark in the space nearest the word dull. If you are sort of undecided, you would place a check mark in the middle space between the two words.

 Now rate each of the activities that follow [only one is listed]:

Working with other students in small groups

friendly :_____:_____:_____:_____:_____:_____:_____:_____: unfriendly

happy :_____:_____:_____:_____:_____:_____:_____:_____: sad

easy :_____:_____:_____:_____:_____:_____:_____:_____: hard

fun :_____:_____:_____:_____:_____:_____:_____:_____: work

hot :_____:_____:_____:_____:_____:_____:_____:_____: cold

good :_____:_____:_____:_____:_____:_____:_____:_____: bad

laugh :_____:_____:_____:_____:_____:_____:_____:_____: cry

beautiful :_____:_____:_____:_____:_____:_____:_____:_____: ugly

5.                  Multidimensional scales

Multidimensional scaling (MDS) is a set of related statistical techniques often used in information visualization for exploring similarities or dissimilarities in data. MDS is a special case of ordination.

Multidimensional scaling (MDS) is a set of data analysis techniques that display the structure of distance-like data as a geometrical picture. It is an extension of the procedure discussed in SCALING.

MDS has its origins in psychometrics. where it was proposed to help understand people's judgments of the similarity of members of a set of objects. Torgerson [18] proposed the first MDS method and coined the term. his work evolving from that of Richardson [11]. MDS has now become a general data analysis technique used in a wide variety of fields.