Measurement in Survey Research
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Transcript Measurement in Survey Research
Measurement in Survey
Research
MKTG 3342
Fall 2008
Professor Edward Fox
Measurement in Survey Research
Measurement is the process of assigning
numbers or labels to the attributes of
objects, persons, states, or events in
accordance with specific rules
The Measurement Process
Research
findings
…which leads
to…
Utilize the
scale
If the evaluation is
satisfactory, the
researcher…
Evaluate the
reliability and
validity of the
scale
…that requires the
researcher to…
Develop
a construct
Identify the
concept of
interest
…which is
used to…
A measurement
scale
…which enables a
researcher to create…
…which is used
to create…
A constitutive
definition
An operational
definition
…which enables
a researcher to
develop …
Steps 1&2: Identify Concept /
Develop Construct
Research
findings
Utilize the
scale
Evaluate the
reliability and
validity of the
scale
Develop
a construct
Identify the
concept of
interest
A measurement
scale
A constitutive
definition
An operational
definition
Steps 1&2: Identify Concept /
Develop Construct
Measurement
begins by identifying a
concept of interest and the construct
to be studied. Both are abstractions of
reality.
A concept is expressed in every-day
terminology. This requires the
researcher to generalize/categorize.
A construct is a theoretical abstraction
that can’t really be observed (e.g.,
love, trust, social class, personality,
power).
Steps 1&2: Identify Concept /
Develop Construct – Example
Question – Why do some customers
buy Air Jordan athletic shoes over and
over again?
Concept – Repeat purchase
Construct – Brand loyalty
Steps 3&4: Define the Concept
Conceptually and Operationally
Research
findings
Utilize the
scale
Evaluate the
reliability and
validity of the
scale
Develop
a construct
Identify the
concept of
interest
A measurement
scale
A constitutive
definition
An operational
definition
Steps 3&4: Define the Concept
Conceptually and Operationally
Constitutive Definition
A
theoretical or conceptual definition that
defines the concept in terms of other
concepts and constructs; like a dictionary
definition
Operational Definition
Defines
which observable characteristics will
be measured and the process for assigning a
value to the concept
Steps 3&4: Define the Concept
Conceptually and Operationally – Example
Constitutive Definition – Increased propensity
to purchase a brand due to previous
experience with that brand
Operational Definition – Rating of purchase
probability, depending upon prior purchase
Step 5: Develop a Measurement
Scale
Research
findings
Utilize the
scale
Evaluate the
reliability and
validity of the
scale
Develop
a construct
Identify the
concept of
interest
A measurement
Scale
A constitutive
definition
An operational
definition
Step 5: Develop a Measurement
Scale
SCALE
A scale is a set of symbols or numbers so
constructed that the symbols or numbers can
be assigned by a rule for the individuals (or
their behaviors or attitudes) to whom the
scale is applied
Types of Scales
Nominal
Description
Uses
numerals to identify objects, individuals,
events, or groups. Used for Classification
(male/female; buyer/nonbuyer)
Typical
Descriptive Statistics
Frequency
Examples
counts, percentages/modes
of Nominal Scales
Gender
Geographic Area
(1) Male
(1) Urban
(3) Suburban
(2) Female
(2) Rural
Types of Scales
Ordinal
Scale
Description
In
addition to identification, the numerals
provide information about the relative amount
of some characteristic; determines greater or
less than
Typical
Descriptive Statistics
Median
Example
of Ordinal Scale:
Please rank the following fax machines from 1 to 5 with 1 being
the most preferred and 5 the least preferred.
_____ Panasonic
_____ Toshiba
_____ Sharp
_____ Savin
_____ Ricoh
Types of Scales
Interval
Description
Has
all the properties of nominal and ordinal
scales + equal intervals between consecutive
points; preferred measure for complex
concepts or constructs
Typical
Descriptive Statistics
Mean/variance
Example
Scaled
of an Interval Scale
response (on a scale from 1 to 10…)
Types of Scales
Ratio
Description
Incorporates
all the properties of nominal,
ordinal, and interval scales plus it includes an
absolute zero point
Typical
Descriptive Statistics
Mean/variance
Example
Age,
+ a few higher order statistics
of a Ratio Scale
weight, height, population of the U.S., etc.
Step 5: Develop a Measurement
Scale – Example
Probability of purchasing the shoe
brand again in the next month, next
year, or at any point in the future
Type of scale?
Step 6: Scale Reliability and
Validity
Research
findings
Utilize the
scale
Evaluate the
reliability and
validity of the
scale
Develop
a construct
Identify the
concept of
interest
A measurement
scale
A constitutive
definition
An operational
definition
Step 6: Scale Reliability and
Validity
Any
measurement can be expressed as a
function of three components:
XO = XT + XS + XR
Observed Score = True Score + Systematic Error + Random Error
Ideally,
In Practice,
XO = XT
XO XT …
that is, XS + XR 0
Total Error = XS + XR, where
XS = Systematic error (validity)
XR = Random error (reliability)
Step 6: Scale Reliability and
Validity – Illustration
Not Reliable
.
.
.
.
.
.
Not Valid
.
. .
.
.......
..
......
.
.
.
Reliable and Valid
Scale Reliability
The degree to which measures are free
from random “noise” and, therefore,
provide consistent data
Issues
Test-Retest Reliability
Internal Reliability (split-half
technique)
Scale Validity
Addresses the issue of whether what we
attempted to measure was actually
measured
Issues
Face
Validity
Content Validity
Predictive Validity
Convergent Validity
Discriminant Validity
Summary
Measurement means using rules to assign
numbers to objects in such a way as to
represent quantities of attributes
The measurement process is as follows:
identify the concept of interest, develop a
construct, define the concept constitutively
and operationally, develop a measurement
scale, evaluate the reliability and validity of
the scale, and then use the scale
There are four basic types of measurement
scales: nominal, ordinal, interval, and ratio
Summary
(Cont.)
Measurement data consists of information
(“signal”) and error (“noise”).
Validity requires that you actually measure
what you intended to measure
Reliability is the degree to which measures
are free from random error