Measurement and Scaling
By:
Dr Manoj Kuamr
Measurement and Scaling
• In the field of business research, a researcher tries to
gather
information
through
administering
questionnaire. In business research the researcher
have to measure the information on certain scale as
per requirement of the research problem.
• Measurement of physical properties is not a complex
deal, whereas measurement of psychological
properties require a careful attention of a researcher.
• What should be measured is of utmost important.
(FIVE POINT SCALE)
• Precise measurement in business research
requires a careful conception careful conceptual
definition, and a system of consistent rules of
assigning scores and numbers (Zikmund, 2007).
Scale of Measurement
• Nominal Scale: When data are labels or names an
used to identify the attribute of an element, the
nominal scale is used.
• Ordinal Scale: In addition to nominal level data
capacities, ordinal scale can be used to rank or order
objects.
• Interval Scale: In internal level measurement, the
difference between the two consecutive number is
meaningful.
• Ratio scale: Ratio level of measurements posses all
the properties of data with meaningful ratio of two
values. Scale of Measurement
The Criteria for Good Measurement
Content
Validity
Criterion
Validity
Validity
Construct
Variability
The Criteria
for Good
Measurement
Test-Retest
Reliability
Reliability
Equivalent
from
Reliability
Sensitivity
Internal
Consistency
Reliability
Concurrent
validity
Predictive
Validity
Convergent
Validity
Discriminant
Validity
Validity
• Validity is the ability of an instrument to measure what it
is designed to measure.
• It sound simple that a measure should measure what is
supposed to measure but has a great deal of difficulty in
real life.
• For example, behaviour of employee to measure
consumer satisfaction in a big mall is a validity issue.
• It is always possible that behaviour of employee is not a
determinant of consumer satisfaction rather various
other factors such as pricing policies, discount policy,
parking facility, quality of the product etc. may be
responsible for consumer satisfaction.
• Hence, the measure designed to measure consumer
satisfaction from employee behaviour may not be a valid
measurement tool.
Content Validity
• The content validation includes, but not limited to,
careful specification of constructs, review of scaling
procedures by content validity judges, and
consultation with experts and the members of the
population.
• Sometimes, it is also referred as face validity.
• In fact, content validity is a subjective evaluation of
the scale for its ability to measure what it supposed
to measure.
• As it is subjective in nature, it alone is not a
sufficient evaluation criterion.
Criterion Validity
• The criterion validity is the ability of the variable to
predict the key variable or criteria. (Lehmann et al.,
1998).
• It involves the determination of whether the scale is
able to perform up to the expectation with respect to
the other variables or criteria.
• Criterion variables may include demographic and
psychographic characteristics, attitudinal and
behavioral measure or scales obtained from other
scales (Malhotra, 2004).
• In accordance with the time sequence, the criterion
validity is classified as a concurrent validity and a
predictive validity.
• Concurrent Validity: if the data collected from
the scale to be evaluated and the data collected
on criterion variable are executed at the same
time and are shown to be valid, then it has
concurrent validity.
• Predictive Validity: if the new measure is able to
predict some future events, then the predictive
validity is said to be established. For example,
the consumer satisfaction measuring instrument
is predictive valid if it followed by sales in near
future.
Construct Validity
• Construct validity is the initial concept, notion,
question, or hypothesis that determines which data
are to be generated and how they are to be gathered
(Golafshani, 2003).
• To evaluate the construct validity, both the theory
and the measuring instrument are considered.
▫ Convergent Validity: A convergent validity is
established new measure correlates or converges with
the other similar measure.
▫ Discriminant Validity: A discriminant validity is
established new measuring instrument has
low
correlation or non-converges with the measure of dissimilar concept.
Multiple Choice Scales
Forced Choice Ranking Scales
Single Item
Scales
Paired Comparison Scales
Constant Sum Scales
Direct Qualification Scales
Q-sort Scales
Measurement Scales
Likert Scales
Multiple Item
Scales
Continuous Rating
Scales
Semantic Differential Scale
Stapel Scales
Numerical Scales