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Catching Up:
Review
Measurement:
“Rules for assigning numbers to objects
(or concepts) to represent quantities of attributes.”
Measurment
Names and symbols are arbitrary.
But to be a true number scale the symbols
must follow some logical
and
systematic arrangement.
Numbers can be assigned using…
Scales:
“A scale is the continuum upon which
measurements are located.”
Some very common scales:
Scales:
Likert Scale
Is a statement (not a question)
followed by five categories of
agreement.
Scales:
Likert Scale
Ice cream is good for breakfast.
1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree
Scales:
Likert Scale
Scales:
Likert Scale
Scales: Likert-like
Scales:
Scales:
Semantic scales:
Typically: Opposite adjectives
separated by 7 selection points.
Scales:
Semantic
scales:
Semantic
scales:
Hybrid
Scales:
Measurement Characteristics:
Measurement characteristics:
Y = x(true) + x(sy-error) + x(random)
Measurement characteristics:
Y = x(true) + x(sy-error) + x(random)
Systematic error can be eliminated.
Measurement characteristics:
Y = x(true) + x(sy-error) + x(random)
Random error cannot be eliminated.
Measurement characteristics:
Y = x(true) + x(sy-error) + x(random)
If a sample is taken to estimate an answer:
another form of error is added……
Measurement characteristics:
This is called a
Sampling Error
Y = x(true) + x(sy-error) + x(random) + x(sampling error)
If you take a sample… you will create a sampling error!
You and a friend (in the same class) take the
same exam at the same time and
get different grades.
WHY?
Take a piece of paper…
write down five different reasons
why these two friends taking the same class
would get different grades...
What then did the grade actually measure?
Write down a definition of a “grade.”
If you suggested that a “grade” is a measurement
of what a student knows, how many “grades” would
you suggest need to be taken in order to be confident that
the student actually knows what the grades indicate
that they know?
Measurement characteristics:
Reliability
Measurement characteristics:
Validity
Before validity can be established, it is necessary to
show that measurements have reliability.
A measurement can be reliable without being
valid, but it cannot be judged to be valid without
reliability.
Measurement characteristics:
Reliability
1. Stability
Measurement characteristics:
Reliability
1. Stability
a. Test-retest
b. Equivalent forms
Measurement characteristics:
Reliability
1. Stability
a. Test-retest
b. Equivalent forms
2. Equivalence
Measurement characteristics:
Reliability
1. Stability
a. Ttest-retest
b. Equivalent forms
2. Equivalence
a. Kuder-Richardson
b. Cronbach’s Alpha
Measurement characteristics:
Reliability
1. Stability
a. Test-retest
b. Equivalent forms
2. Equivalence
a. Kuder-Richardson
b. Cronbach’s Alpha
Lee Cronbach
Measurement characteristics:
Reliability
1. Stability
a. Test-retest
b. Equivalent forms
2. Equivalence
a. Kuder-Richardson
b. Cronbach’s Alpha
Learn, Effective, & Like the instructor
Measurement characteristics:
Reliability
1. Stability
a. Test-retest
b. Equivalent forms
2. Equivalence
a. Kuder-Richardson
b. Cronbach’s Alpha
3. Inter-rater Consistency
a. Krippendorff’s Alpha
Klaus Krippendorff
1932 -
The reliability coefficient is simply a proportion.
It is the ratio of
the true variance over the total variance created by the instrument.
If rxx = 0.70, then 70% of the variance
of the instrument can be seen
as being created by what was being measured,
and 30% by everything else.
Measurement characteristics:
If a measurement is reliable, it
may be valid:
But there are many ways that
a measurement could be valid or invalid.
Measurement characteristics:
Validity
1. Face validity
Measurement characteristics:
Validity
1. Face
2. Content
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
4. Construct
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
4. Construct
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
4. Construct
a. Convergent
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
4. Construct
a. Convergent
b. Divergent
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
4. Construct
a. Convergent
b. Divergent
c. Discriminant
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
4. Construct
a. Convergent
b. Divergent
c. Discriminant
d. Nomological
Measurement characteristics:
Validity
1. Face
2. Content
3. Criteria
a. Concurrent
b. Predictive
4. Construct
5. Utilitarian (?)
A measurement may satisfy a utilitarian goal
independently of any validity of the actual measurement.
It is very important
that we can measure
Hypothetical Constructs!
In practical terms, a construct is defined by
HOW it is measured.
This is called an:
“Operational
Definition.”
Is an electron a particle
or
Is it a wave?
That depends upon how it is measured!
http://chemwiki.ucdavis.edu/Physical_Chemistry/Quantum_Mechanics/Atomic_Theory/Electrons_in_Atoms/Wave-Particle_Duality
Percy W. Bridgman 1882-1961
Operationalization is the process of defining a fuzzy concept so as to
make the concept measurable in form of variables consisting of specific
observations. In a wider sense it refers to the process of specifying the
extension of a concept.
Intelligence could be defined as how fast (RT)
a person solves a puzzle….
Or intelligence could be defined as not
getting cheated at the car dealership.