Transcript Chapter 01 - Baylor University

Chapter 9
Understanding Measurement
Carl McDaniel, Jr.
Roger Gates
Slides Prepared by
Bruce R. Barringer
University of Central Florida
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-1
Learning Objectives
• To understand the concept of measurement.
• To learn about the measurement process and
how to develop a good measurement.
• To understand the four levels of scales and
their typical usage.
• To become aware of the concepts of
reliability and validity.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-2
The Concept of Measurement
Measurement is the process of assigning
numbers or labels to objects, persons, states, or
events in accordance with specific rules to
represent quantities or qualities of attributes.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-3
Rule Defined
A rule is a guide, a method, or a command that
tells a researcher what to do.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-4
The Measurement Process
Which leads to
If the evaluation is
satisfactory, the
researcher
utilizes the
scales
research
findings
Use the concept to
Which is used
to create
Identify the
concept of
interest
evaluate the
reliability and the
validity of the
scales
That require the
researcher to
Develop
a construct
measurement
scales
a constitutive
definition
operational
definition
Which enables a
researcher to
develop an
Which enables a
researcher to create
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-5
Step One: Identify the Concept of
Interest
• Measurement begins by identifying a
concept of interest for study.
– A concept is an abstract idea generalized from
particular facts.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-6
Step Two: Develop a Construct
• Constructs are specific types of concepts
that exist at higher levels of abstraction.
– Constructs are invented for theoretical use.
– The value of specific constructs depends on
how useful they are in explaining, predicting,
and controlling phenomena, just as the value of
everyday concepts depends on how much they
assist us in everyday affairs.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-7
Steps Three and Four: Define the Concept
Both Constitutively and Operationally
Slide 1 of 2
• Constitutive
– A constitutive (or theoretical or conceptual)
definition defines a concept with other concepts
and constructs, establishing boundaries for the
construct under study; it states the central idea
or concept under study.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-8
Steps Three and Four: Define the Concept
Both Constitutively and Operationally
Slide 2 of 2
• Operational Definition
– An operational definition defines which
observable characteristics will be measured and
the process for assigning a value to the concept.
– In other words, an operational definition serves
as a bridge between a theoretical concept and
real-world events or factors.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-9
Step Five: 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 to the individuals (or their
behaviors or attitudes) to whom the scale is
applied.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-10
Types of Scales
Slide 1 of 8
• Nominal Scale
– Description
• Uses numerals to identify objects, individuals,
events, or groups.
– Basic Empirical Operations
• Determination of equality/inequality
– Typical Usage
• Classification (male/female; buyer/nonbuyer)
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-11
Types of Scales
Slide 2 of 8
• Nominal Scale (continued)
– Typical Descriptive Statistics
• Frequency Counts, percentages/modes
– Example of Nominal Scale
• Sex
• Geographic Area
(1) Male (2) Female
(1) Urban (2) Rural (3) Suburban
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-12
Types of Scales
Slide 3 of 8
• Ordinal Scale
– Description
• In addition to identification, the numerals provide
information about the relative amount of some
characteristic posed by an event, object, etc.
• Basic Empirical Operations
• Determination of greater or less.
– Typical Usage
• Rankings/ratings
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-13
Types of Scales
Slide 4 of 8
• Ordinal Scale (continued)
– Typical Descriptive Statistics
• Median (mean and variance metric)
– 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
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-14
Types of Scales
Slide 5 of 8
• Interval Scale
– Description
• Possesses all the properties of nominal and ordinal
scales plus the intervals between consecutive points
are equal.
– Basic Empirical Operations
• Determination of equality of intervals.
– Typical Usage
• Preferred measure of complex concepts/constructs.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-15
Types of Scales
Slide 6 of 8
• Interval Scale (continued)
– Typical Descriptive Statistics
• Mean/variance
– Example of an Interval Scale
• Thermometer
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-16
Types of Scales
Slide 7 of 8
• Ratio Scale
– Description
• Incorporates all the properties of nominal, ordinal,
and interval scales plus it includes an absolute zero
point.
– Basic Empirical Operations
• Determination of equality of ratios.
– Typical Usage
• When precision instruments are available.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-17
Types of Scales
Slide 8 of 8
• Ratio Scale (continued)
– Typical Descriptive Statistics
• Mean.
– Example of a Ratio Scale
• Age, weight, height, population of the U.S., etc.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-18
Step Six: Evaluate the Reliability
and Validity of the Measures
• Reliability
– Is the degree to which measures are free from
random error and, therefore, provide consistent
data.
• Validity
– Validity addresses the issue of whether what we
try to measure was actually measured.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-19
Assessing the Reliability of a
Measurement Instrument
Test-Retest Reliability
Use the same instrument a second time
under nearly the same conditions as possible.
Equivalent Form Reliability
Use two instruments that are as similar as
possible to measure the same object during
the same time period.
Internal Consistency
Reliability
Compare different samples of items being
used to measure a phenomenon during the
same time period.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-20
Assessing the Validity of a
Measurement Instrument
Slide 1 of 2
Face Validity
Researchers judge the degree to which a
measurement instrument seems to measure
what it is supposed to.
Content Validity
The degree to which the instrument items
represent the universe of the concept under
study.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-21
Assessing the Validity of a
Measurement Instrument
Slide 1 of 2
Criterion-related Validity
The degree to which a measurement instrument
can predict a variable that is designed a
criterion.
A. Predictive Validity- The extent to which a
future level of a criterion variable can be
predicted by a current measurement on a
scale.
B. Concurrent Validity- The extent to which
a criterion variable measured at the same
point in time as the variable of interest can
be predicted by the measurement instrument.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-22
Assessing the Validity of a
Measurement Instrument
Slide 2 of 2
Construct Validity
The degree to which a measure confirms a
hypothesis created from a theory based upon the
concepts under study.
A. Convergent validity - The degree of
association among different measurement
instruments that purport to measure the same
concept.
B. Discriminant Validity - The lack of
association among constructs that are
supposed to be different.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-23
Illustrations of Possible Reliability and
Validity Situations in Measurement
Situation 1
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.
.
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Situation 2
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Situation 3
.........
. .
.
.. .
..
.
.
Neither reliable
nor valid
Highly reliable
but not valid
Highly reliable
and valid
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-24
Summary of Key Points
Slide 1 of 3
• Measurement consists of using rules to
assign numbers to objects in such a way as
to represent quantities of attributes.
• A measurement rule is a guide, a method, or
command that tells the researcher what to
do.
• Accurate measurement requires rules that
are both clear and specific.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-25
Summary of Key Points
Slide 2 of 3
• 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 levels of measurement:
nominal, ordinal, interval, and ratio.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-26
Summary
Slide 3 of 3
• Measurement data consists of accurate
information and errors.
• Reliability is the degree to which measures
are free from random error and therefore
provide consistent data.
• Validity refers to the notion of actually
measuring what we are attempting to
measure.
© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e
Slide 9-27