Measurement is the process observing and recording the observations that are collected as part of a research effort.  Process of assigning numbers to objects or observations, the level of measurement being a function of the rules under which the numbers are assigned.  “convert the basic materials of the problem to data”

1. SCALING AND
MEASUREMENT
TECHNIQUE
PRESENTED
BY:
SID G

2. LEARNINGS:
• MEASUREMENT CONCEPT
• NEED OF MEASUREMENT
• PROBLEM IN MEASUREMENT IN
MANAGEMENT RESEARCH: validity and
reliability
• LEVEL OF MEASUREMENT
o NOMINAL
o ORDINAL
o INTERVAL
o RATIO

3. Measurement is the process observing and
recording the observations that are collected as
part of a research effort.
Process of assigning numbers to objects or
observations, the level of measurement being a
function of the rules under which the numbers
are assigned.
“convert the basic materials of the problem to
data”

4. • Measurement is the process of systematically
assigning numbers to objects and their
properties, to facilitate the use of mathematics in
studying and describing objects and their
relationships
• According to Maxim (1999), measurement is a
process of mapping empirical phenomena with
using system of numbers.
• researchers can interpret the data with
quantitative conclusion which leads to more
accurate and standardized outcomes

5. It is easy to assign numbers in respect
of properties of some objects, but it is
relatively difficult in respect of others.
For instance, measuring such things
as social conformity, intelligence, or
marital adjustment is much less
obvious and requires much closer
attention than measuring physical
weight, biological age or a person’s
financial assets.

6. In other words, properties like weight,
height, etc., can be measured directly with
some standard unit of measurement, but it is
not that easy to measure properties like
motivation to succeed, ability to stand stress
and the like. We can expect high accuracy in
measuring the length of pipe with a yard
stick, but if the concept is abstract and the
measurement tools are not standardized, we
are less confident about the accuracy of the
results of measurement.

7. PROBLEMS IN MEASUREMENT IN
MANAGEMENT RESEARCH
• PARTICIPANT ERROR
• PARTICIPANT BIAS
• RESEARCHER ERROR
• RESEARCHER BIAS

8. LEVELS OF MEASUREMENT
• Measurement scales in Research Methodology
are used to categorize and/or quantify
variables.From what has been stated above, we
can write that scales of measurement can be
considered in terms of their mathematical
properties

9. The most widely used classification of
measurement scales are:
• Nominal scale
• Ordinal scale
• Interval scale and
• Ratio scale

10. Nominal scale
• Nominal scale is simply a system of assigning
number symbols to events in order to label them
• Numbers cannot be considered to be associated
with an ordered scale for their order is of no
consequence;
• The numbers are just convenient labels for the
particular class of events and as such have no
quantitative value

11. Nominal scale is the least powerful level of
measurement. It indicates no order or distance
relationship and has no arithmetic origin. A
nominal scale simply describes differences
between things by assigning them to categories.
Nominal data are, thus, counted data. The scale
wastes any information that we may have about
varying degrees of attitude, skills,
understandings, etc. In spite of all this, nominal
scales are still very useful and are widely used in
surveys and other ex-post-facto research when
data are being classified by major sub-groups of
the population.

12. Ordinal scale
• The lowest level of the ordered scale that is
commonly used is the ordinal scale. The ordinal
scale places events in order, but there is no
attempt to make the intervals of the scale equal
in terms of some rule. Rank orders represent
ordinal scales and are frequently used in
research relating to qualitative phenomena

13. • Thus, the use of an ordinal scale implies a
statement of ‘greater than’ or ‘less than’ (an
equality statement is also acceptable) without our
being able to state how much greater or less. The
real difference between ranks 1 and 2 may be more
or less than the difference between ranks 5 and 6.
Since the numbers of this scale have only a rank
meaning, the appropriate measure of central
tendency is the median. A percentile or quartile
measure is used for measuring dispersion.
Correlations are restricted to various rank order
methods. Measures of statistical significance are
restricted to the non-parametric methods.

14. Interval scale
• In the case of interval scale, the intervals are
adjusted in terms of some rule that has been
established as a basis for making the units equal.
The units are equal only in so far as one accepts
the assumptions on which the rule is based.
• Interval scales can have an arbitrary zero, but it is
not possible to determine for them what may be
called an absolute zero or the unique origin.
• The primary limitation of the interval scale is the
lack of a true zero; it does not have the capacity to
measure the complete absence of a trait or
characteristic.

15. • The Fahrenheit scale is an example of an interval
scale and shows similarities in what one can and
cannot do with it. One can say that an increase
in temperature from 30° to 40° involves the
same increase in temperature as an increase
from 60° to 70°, but one cannot say that the
temperature of 60° is twice as warm as the
temperature of 30° because both numbers are
dependent on the fact that the zero on the scale
is set arbitrarily at the temperature of the
freezing point of water. The ratio of the two
temperatures, 30° and 60°, means nothing
because zero is an arbitrary point.

16. Ratio scale
• The ratio involved does have significance and facilitates a kind of
comparison which is not possible in case of an interval scale.
• the highest form of measurement that meets all the rules of othe
r forms of measure; it includes
mutually exclusive categories, exhaustive categories, rank orderi
ng, equal spacing between intervals, and a continuum of
values. Ratio level measurement also includes a value of zero.
• Ratio scale represents the actual amounts of variables. Measures
of physical dimensions such as weight, height, distance, etc. are
examples.

17. Errors in Measurement in Research
Methodology
• Errors in Measurement should be precise and
unambiguous in an ideal research study. This
objective, however, is often not met with in
entirety. As such the researcher must be aware
about the sources of error in measurement. The
following are the possible sources of error in
measurement.

18. Reliability and validity
• In evaluating a measurement method, consider
two general dimensions: reliability and validity.

19. RELIABILITY
• Reliability refers to the consistency of a
measure.
• Psychologists consider three types of
consistency:
I. over time (test-retest reliability),
II. across items (internal consistency), and
III.across different researchers (inter-rater
reliability).

20. Test-Retest Reliability
• When researchers measure a construct that they
assume to be consistent across time, then the scores
they obtain should also be consistent across time
• Assessing test-retest reliability requires using the
measure on a group of people at one time, using it
again on the same group of people at a later time,
and then looking at test-
retest correlation between the two sets of
scores. .

21. This is typically done by
graphing the data in a scatter
plot and computing Pearson’s r.
shows the correlation between
two sets of scores

22. Internal Consistency
• A second kind of reliability is
internal consistency, which is the consistency
of people’s responses across the items on a
multiple-item measure. In general, all the items
on such measures are supposed to reflect the
same underlying construct, so people’s scores on
those items should be correlated with each
other.

23. • internal consistency can only be assessed by
collecting and analyzing data. One approach is to
look at a split-half correlation. This involves
splitting the items into two sets, such as the first
and second halves of the items or the even- and
odd-numbered items. Then a score is computed
for each set of items, and the relationship between
the two sets of scores is examined
• the split-half correlation between several
university students’ scores on the even-numbered
items and their scores on the odd-numbered items
of the Rosenberg Self-Esteem Scale.
Pearson’s r for these data is +.88. A split-half
correlation of +.80 or greater is generally
considered good internal consistency.

24. • Perhaps the most common measure of internal
consistency used by researchers in psychology is
a statistic called Cronbach’s α (the Greek letter
alpha). Conceptually, α is the mean of all
possible split-half correlations for a set of items.

25. Interrater Reliability
• Many behavioral measures involve
significant judgment on the part of an
observer or a rater. Inter-
rater reliability is the extent to which
different observers are consistent in their
judgments.
• For Example: customer behaviour
by different observers

26. VALIDITY
• Validity simply means that a test or instrument is
accurately measuring what it’s supposed to.
Face Validity is the most basic type of validity and it
is associated with a highest level of subjectivity
because it is not based on any scientific approach. In
other words, in this case a test may be specified as
valid by a researcher because it may seem as valid,
without an in-depth scientific justification.
• Example: questionnaire design for a study that
analyses the issues of employee performance can be
assessed as valid because each individual question
may seem to be addressing specific and relevant
aspects of employee performance.

27. Construct Validity
Relates to assessment of suitability of measurement
tool to measure the phenomenon being studied.
Application of construct validity can be effectively
facilitated with the involvement of panel of ‘experts’
closely familiar with the measure and the
phenomenon.
• Example: with the application of construct validity
the levels of leadership competency in any given
organization can be effectively assessed by devising
questionnaire to be answered by operational level
employees and asking questions about the levels of
their motivation to do their duties in a daily basis.

28. Criterion-Related Validity
Involves comparison of tests results with the outcome.
This specific type of validity correlates results of
assessment with another criterion of assessment.
Example: nature of customer perception of brand
image of a specific company can be assessed via
organising a focus group. The same issue can also be
assessed through devising questionnaire to be
answered by current and potential customers of the
brand. The higher the level of correlation between
focus group and questionnaire findings, the high the
level of criterion-related validity.

29. • Formative Validity refers to assessment of
effectiveness of the measure in terms of
providing information that can be used to
improve specific aspects of the phenomenon.
• Example: when developing initiatives to increase
the levels of effectiveness of organizational
culture if the measure is able to identify specific
weaknesses of organizational culture such as
employee-manager communication barriers,
then the level of formative validity of the
measure can be assessed as adequate.

30. Sampling Validity:
• (similar to content validity) ensures that the area of
coverage of the measure within the research area is
vast. No measure is able to cover all items and
elements within the phenomenon, therefore,
important items and elements are selected using a
specific pattern of sampling method depending on
aims and objectives of the study.
• Example: when assessing a leadership style exercised
in a specific organisation, assessment of decision-
making style would not suffice, and other issues
related to leadership style such as organisational
culture, personality of leaders, the nature of the
industry etc. need to be taken into account as well.

31. SCALING
“The procedure of measuring and
assigning the objects to the numbers
according to the specified rules. In
other words, the process of locating
the measured objects on the
continuum, a continuous sequence of
numbers to which the objects are
assigned is called as scaling.”

32. SCALING TECHNIQUES
• COMPARATIVE SCALE
Paired Comparison Scaling
Rank Order Scaling
Constant Sum Scaling
Q-Sort Scaling
• NON-COMPARATIVE SCALE
• Continuous Rating Scale
• Itemized Rating Scale