QUALITATIVE AND QUANTITATIVE MEASUREMENTtime appears to answer inconsistently or to have a
contradictory opinion.
We often combine many Likert-scaled attitude
indicators into an index. Scale and indexes can
improve reliability and validity. An index uses
multiple indicators, which improves reliability. The
use of multiple indicators that measure several as-
pects of a construct or opinion improves content
validity. Finally, the index scores give a more
precise quantitative measure of a person’s opinion.
For example, we can measure a person’s opinion
with a number from 10 to 40 instead of in four
categories: “strongly agree,” “agree,” “disagree,”
and “strongly disagree.”
Instead of scoring Likert items, as in the previ-
ous example, we could use the scores –2, –1, +1, +2.
This scoring has an advantage in that a zero implies
neutrality or complete ambiguity whereas a high
negative number means an attitude that opposes the
opinion represented by a high positive number.
The numbers we assign to the response cate-
gories are arbitrary. Remember that the use of a zero
does not give the scale or index a ratio level of mea-
surement. Likert scale measures are at the ordinal
level of measurement because responses indicate
only a ranking. Instead of 1 to 4 or –2 to +2, the
numbers 100, 70, 50, and 5 would have worked.
Also, we should not be fooled into thinking that the
distances between the ordinal categories are inter-
vals just because numbers are assigned. The num-
bers are used for convenience only. The
fundamental measurement is only ordinal.^20
The real strength of the Likert Scale is its sim-
plicity and ease of use. When we combine several
ranked items, we get a more comprehensive mul-
tiple indicator measurement. The scale has two lim-
itations: Different combinations of several scale
items produce the same overall score, and the re-
sponse set is a potential danger.
2.Thurstone scaling.This scale is for situa-
tions when we are interested in something with
many ordinal aspects but would like a measure that
combines all information into a single interval-level
continuum. For example, a dry cleaning business,
Quick and Clean, contacts us; the company wants
to identify its image in Greentown compared to that
of its major competitor, Friendly Cleaners. We con-
ceptualize a person’s attitude toward the business as
having four aspects: attitude toward location, hours,
service, and cost. We learn that people see Quick
and Clean as having more convenient hours and lo-
cations but higher costs and discourteous service.
People see Friendly Cleaners as having low cost and
friendly service but inconvenient hours and loca-
tions. Unless we know how the four aspects relate
to the core attitude—image of the dry cleaner—we
cannot say which business is generally viewed
more favorably. During the late 1920s, Louis Thur-
stone developed scaling methods for assigning
numerical values in such situations. These are now
called Thurstone scalingor the method of equal-
appearing intervals.^21
Thurstone scaling uses the law of comparative
judgment to address the issue of comparing ordinal
attitudes when each person makes a unique judg-
ment. The law anchors or fixes the position of one
person’s attitude relative to that of others as each
makes an individual judgment. The law of compar-
ative judgment states that we can identify the “most
common response” for each object or concept being
judged. Although different people arrive at differ-
ent judgments, the individual judgments cluster
around a single most common response. The dis-
persion of individual judgments around the com-
mon response follows a statistical pattern called the
normal distribution. According to the law, if many
people agree that two objects differ, then the most
common responses for the two objects will be dis-
tant from each other. By contrast, if many people
are confused or disagree, the common responses of
the two objects will be closer to each other.
With Thurstone scaling, we develop many state-
ments (e.g., more than 100) regarding the object of
interest and then use judges to reduce the number to
a smaller set (e.g., 20) by eliminating ambiguousThurstone scaling Measuring in which the re-
searcher gives a group of judges many items and asks
them to sort the items into categories along a contin-
uum and then considers the sorting results to select
items on which the judges agree.