This document discusses measurement and scaling in research. It defines measurement as assigning numbers or symbols to characteristics of objects according to rules. Scaling is creating a continuum to locate objects by amount of characteristic. There are four main types of scales - nominal, ordinal, interval, and ratio - which determine appropriate statistical tests. The document also discusses issues in designing single and multiple item scales for measurement and provides guidelines for developing reliable and valid multi-item scales.

1. MEASUREMENT AND
SCALING
Prof M. R. Suresh

2. Measurement: defined as a standardized
process of assigning numbers or other
symbols to certain characteristics of objects of
interest according to prespecified rules.
•important as statistical analyses can be done
on appropriate scales
•two characteristics:
–one-to-one correspondence between the
symbol and the characteristic (in the object)
being measured
–rules of assignment must be invariant over
time

3. Scaling is a process of creating a continuum
on which objects are located according to the
amount of measured characteristic they
possess
Type of Scale Statistical Tests
Nominal Percentage, mode, chi-square
Ordinal Percentile, median Rank-Order
Correlation Friedman’s ANOVA
Interval Mean, , t-test, ANOVA,
Regression analysis correlation
Ratio G.M, H.M. coefficient of variation

4. Nominal Scale
objects are assigned to mutually exclusive,
labeled categories
E.g. Male, female, Geographical area
if one entity is assigned the same number as
another, they are identical with respect to a
nominal variable
Ordinal Scale
obtained by ranking objects or arranging
them in order with respect to some common
variable
E.g. Ranks of students, seniors, juniors in a
college

5. Interval Scale
•in this the numbers used to rank the objects
represent equal increments of attribute being
measured
•differences can be compared
•difference between 2 & 3 same as 6 & 7
•no absolute zero
•ratios of differences can be compared
E.g. attitude measures, indices, temperature scales
Ratio Scale
•meaningful zero point
•makes comparisons in absolute magnitude
•measuring public opinion

6. Issues in Designing Single – item
Scales
1. Number of scale categories 2 to 
capability, format, object attribute
2. Types of poles
verbal descriptors as endpoints
e.g. sweet ----- not sweet
3. Strength of anchors
extremely colorful, very colorful
4. Labeling
5. Balancing

7. Single Item Scales
only one item to measure a construct
1. Itemized category scale
Satisfaction with present health
insurance plan
- very satisfied
- quite satisfied
- somewhat satisfied
- not at all satisfied
Very satisfied Very dissatisfied
+2 +1 0 -1 -2

8. 2. Comparative scales
E.g.
Rank-Order Scales
•require respondents to arrange a set of
objects with respect to common criterion
Two problems – forced to make a choice,
undifferentiated middle
Constant sum scale
Limitation – only a few categories
Q – sort scaling
Paired – comparison

9. Multiple Item Scales
Objects have many facets
Likert scale also known as summated scale
degree of agreement/disagreement on a
variety of statements
two parts : item part, evaluative part
important assumption: single common factor
Thurstone scale also called equal appearing
intervals group of judges are given 75 to 100
items degree of favourableness (11 category
bipolar)
scale value of each items is the median value
assigned by judges complicated

10. •Semantic Differential widely used
e.g. images of competing brands preference of
bipolar scales pairs of objects/phrases correspond to
product/service attributes -ve or unfavorable pole
rotated treated as interval scales, group mean values
calculated
specific information can be lost
•Profile analysis a variation
•Stapel scales
Unipolar +3/ +2/ +1
Tangy -1/ -1/ -1
•Associative scaling
Appropriate for choice situation in a sequential
decision process trade – offs not captured reduced
validity

11. Guidelines for developing multi-item
scale
1. Determine what you want to measure
2. Generate as many items as possible
3. Expert evaluation of initial pool of items
4. Determine type of attitudinal scale to be
used
5. Include validation items
6. Administer items to an initial sample
7. Refine
8. Optimize scale length

12. Choice of an attitudinal scale
specific info required to satisfy
research objectives
adaptability of scale to data
collection method, budget
compatibility to respondent

13. Accuracy of attitude measurements
True Score Model
XO = XT + XS (affects in a constant way)
+ XR (transient factor {situational})
Validity
Content/face validity: subjective but
systematic evaluation of how well the
content of a scale represents the
measurement task

14. Criterion validity: reflects whether
a scale performs as expected in
related to other variables selected
(criterion)
•concurrent validity
•predictive validity
Construct Validity
•convergent validity
•discriminant validity

15. •Reliability
test – retest
split half
•Sensitivity: ability to discriminate
among meaningful differences in
altitudes
•Generalizability
•Relevancy
Relevance = reliability X validity
•International MR

16. Source: Mainly from Marketing Research: Aaker, Kumar & Day, John Wiley & Sons, Latest Asian
Edn.
Business Research Methods- A South Asian Perspective, Zikmund, Babin, Carr, Adhikari and
Griffin, Cengage Learning
For details refer book. For academic discussion at SDMIMD only