measurement scales and attitudes
TRANSCRIPT
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Measurement, Scales and
Attitudes
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Nominal
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Ordinal?
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Interval
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Ratio
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Types of Scales
Nominal - Identification only
Ex (players numbers, male=1 female=0)
Ordinal -Ranking
Ex (grades?) SEI score
IntervalRanks and distinguishes intervals
Ex (temperature)
Ratioabsolute quantities
Ex (weight, degrees Kelvin)
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You Try
Which college is your major housed in?
1. CLS 2. CBA 3. SAH
How much money did you spend on alcohol at
the bars in the last 7 days?_____Dollars
Or answer categories
1. $0-10 2. $11-20 3. $21 +
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Practice Problems
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Appropriate Statistical Analysis
Scale matters.
Usually
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Index Measures
Conglomerates of questions
Mapping multiple responses to a single metric
Consumer Sentiment Index
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Good Measurement
Reliable
Valid
Sensitive
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Wrong
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Validity-reliability bulls eye (Babbie, 1998)
Both
valid & reliable Reliable,
but invalid
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Reliability
Degree to which measures are free from error
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Reliability
Repeatability
Test-Retest method- High correlation suggests
stability/reliability
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Reliability
Internal Consistency
Split-half method- take results form even
questions and compare to odd number questions
Equivalent form- asking different but equivalent
questions of a group, and comparing their
answers on the separate questions
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Validity
the ability to measure that which you intend
to measure
Reliability is a necessarycondition for validity,
not sufficient
Example - if the scale always reads 5 pounds too
much. It is reliable, but not a valid measure of
weight.
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Types of Validity
Content (Face) validity- agreement that a scaleaccurately measures that which it is intendedto
Criterion validity- the ability of a measure tocorrelate highly with another measure of thesame construct
Concurrent validity- measures made concurrently
Predictive validity- correlates with future measure
Construct validity- The ability of a measure toconfirm a network of related hypothesis
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Types of Validity
Content (Face) validity- agreement that a scale
accurately measures that which it is intended
to
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Types of Validity
Criterion validity- the ability of a measure to
correlate highly with another measure of the
same construct
Concurrent validity- measures made concurrently
Predictive validity- correlates with future measure
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Types of Validity
Construct validity- The ability of a measure to
confirm a network of related hypothesis
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Sensitivity
a measurements ability to measure variability
in stimuli
Without variability in response we have
nothing of interest.
We can classify but not understand or explain
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Attitude Measurement
Attitudean enduring disposition which
contains these components:
Affective (emotional)
Cognitive (reason)
Behavioral (action)
Example (sexual identity)
Hypothetical Construct
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Male Sex Behavior and
Identification
Total 33 10 1 213 1 256normal/straight 1 0 64 65something else 1 2 4 7bisexual 4 3 1 8
homosexual 22 0 2 24heterosexual 5 5 1 142 1 152
identification exclusive both male exclusive Total rs sexual year gender of sex ps in the last
Col1 exclusively male
Col 2 both
Col 3 exclusively female
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Female Sex Behavior and
Identification
Col1 exclusively male
Col 2 both
Col 3 exclusively female
Total 1 531 7 19 1 557normal/straight 87 1 0 88something else 7 0 5 12
bisexual 4 2 2 8homosexual 1 0 8 9heterosexual 1 432 4 4 1 440
identification exclusive both male exclusive Total rs sexual year gender of sex ps in the last. tab sxident sexsex if gender==0
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Male Sexual Attraction and
Identification
Total 1 396 43 9 11 37 1 496normal/straight 74 2 0 0 3 79something else 5 1 2 2 1 11
bisexual 2 3 5 1 0 11homosexual 1 1 0 8 17 27
heterosexual 1 314 36 2 0 16 1 368identification only wome mostly wo both wome mostly me only men Total
rs sexual is r attracted to males or females
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Female Sexual Attraction and
Identification
Total 7 11 15 50 1 803 1 886normal/straight 1 0 0 0 116 117something else 3 0 1 1 7 12
bisexual 0 2 5 3 0 10homosexual 2 9 1 0 0 12heterosexual 1 0 8 46 1 680 1 735
identification only wome mostly wo both wome mostly me only men Total rs sexual is r attracted to males or females. tab sxident attract if gender==0
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Practice Problems
Drinking Alcohol
Religion
Music
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Concept Measurement
Awareness:measure of knowledge; understanding;familiarity
Behavior:measure of actions/choices that took place
Motivation:measure of why people behave as they do
Opinion:measure of belief or attitude Preference:measure of likes/dislikes
Desire:measure of wants
Interest:measure of concerns/curiosities
Intention:measure of anticipated behavior Demographic:measure of respondents characteristics
Perceptions of above?
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What is Most Appropriate?
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Methods of Measuring Attitudes
Rating
Likert Scalecarefully constructed attitudinal
measure which asks people for their agreement
with a statement
Example: Please rate each of the following, on a
scale from 1 to 10, with 1 being least importantand 10 being most important
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Methods of Measuring Attitudes
Ranking
Rank choices from most important to least
important
Example: Of the following 10 items please
rank them in order of importance, with 1
being least important and 10 being mostimportant.
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Source: http://blog.vovici.com/blog/bid/18228/Ranking-Questions-vs-Rating-Questions
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Sorting
Asks respondents to sort items/names into groups
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Multiple Choice
Provide alternative responses that R might
choose.
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Monadic
Q. How satisfied are you with your current
job?
1. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied
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Comparative
Q. Compared to your current job how much
responsibility did you have at your last job?
1. More
2. About the Same
3. Less
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How many categories are needed?
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Balanced
Q. How satisfied are you with your current cable
service?
1. Very Satisfied2. Somewhat Satisfied
3. Somewhat unsatisfied
4. Very unsatisfied
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Unbalanced
Q. How satisfied are you with your current cable
service?
1. Very Satisfied2. Somewhat Satisfied
3. Somewhat unsatisfied
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Forced Choice
Does not allow the respondent to offer no
opinion, which is different than a neutral
opinion
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Unforced Choice
Allows respondents to opt out of providing an
opinion.
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JOHN ALLEN PAULOS
Unless we know how things are counted, we
dont know if its wise to count on the numbers.
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Albert Einstein
Not everything that can be counted counts,
and not everything that counts can be
counted.