ATTITUDE SCALING

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LECTURE 4

• ATTITUDE SCALING

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THURSTONE SCALING

• Post WWI work on interests and attitudes during
  1920s- both industrial and psychological research
  interests
• Thurstone proposed model based on jnd
• Assumed interval scale possible for respondents
  to respond to different stimuli
• Developed procedure to generate about 20
  statements that a respondent would agree or
  disagree with, sum the items based on their
  interval scale value (positive or negative items,
  scored appropriately)

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THURSTONE SCALING

• Example Attitude toward Abortion
• 10 statements positive toward abortion
• 10 statements negative toward abortion
• Respondent agreeing with positive statement
  receives 1 point for each
• Respondent disagreeing with negative statement
  receives 1 point each
• Possible range 0 - 20

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THURSTONE SCALING

• A. Select single concept, idea, or construct for
  scaling
• eg. War, marriage, abortion, mathematics
• B. Collect 100-200 statements about the concept
  non-factual, opinion-oriented C. Select about
  80-100 for analysis. eg
• I like arithmetic most of the time.
• Abortions should never be performed under any
  circumstances.
• War is usually a good thing, everything
  considered.

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THURSTONE SCALING

• D. Place statements along 11 point continuum from
  (-) 1 most negative statement to () 11 most
  positive statement, with 6 neutral or
  nonjudgmental statement.
• - use 50-200 subjects to do placement
• - evaluate distribution of each statement

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THURSTONE SCALING

• Median of item as scale value
• for example, statement Abortions should never
  be performed.
• 1 2 3 4 5 6 ...
• n 150 50 0 0
  0 0
• ?
• ile 50
• score 1.17

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THURSTONE SCALING

• for example, statement Abortions should be
  performed only to save the life of the mother.
• 1 2 3 4 5 6...
• n 10 40 90 40
  20 0
• ?
• ile 50
• score 3.05

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THURSTONE SCALING

• Variability
• Eliminate items with ranges gt 6 or 7
• Examine conditional distributions of adjacent or
  close items
• Give items to 200-300 respondents to endorse each
  statement () agree or (-) disagree
• Examine joint endorsements of one item (a) with
  another (b), using an index such as Ia,b nab
  / nb

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THURSTONE SCALING

• The distribution of the aIb s should decrease
  around item a on either side of its scale value
• that is, items with similar scale values should
  have a high similarity index, while items
  further away on the scale should have scale
  values that drop away with distance.
• Throw out items with poor characteristics.

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I n d e x of S i m i l a r I t y
ItemScale Value 5.5
1 2 3 4 5 6 7
8 ? 9 10 11
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LIKERT SCALING

• Renses Likert (1930s) researched the Thurstone
  procedure
• - Placement, scale valuation procedure is
  cumbersome
• - Likert replaced it with
• 1strongly disagree
• 2disagree
• 3uncertain
• 4agree
• 5strongly agree

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LIKERT SCALING

• Give items to sample of target population
• Use classical techniques to select items
• item mean, SD, interitem correlation
• Theoretical justification items are samples of
  the normal distribution shifted along the 1-5
  continuum so that the mean is at the scale value

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Item with scale value 1.5
1 2 3 4
5
14
Item with scale value 3.0
1 2 3 4
5
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RATING SCALES

• Derivatives of Likert scaling
• Alternative adjective set (1..5)
• Requires distributional validation
• Even points is problematic
• Less well investigated

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RATING SCALE VALUES

• Number of scale values
• 1 to 5 based on Likert
• 7, 9, or 11 can be useful for finer
  discriminations
• Dependent on population, concept being assessed

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SEMANTIC DIFFERENTIAL

• Osgood, Suci, Tannenbaum
• Bipolar adjective pairs
• Represent
• Strength strong-weak, heavy-light
• Value good-bad, useful-useless
• Activity fast-slow, hot-cold
• Two factors usually found Evaluation and
  Activity/Strength

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SOME ADDITIONAL IDEAS

• NON-NORMAL DISTRIBUTIONS
• POISSON AND COUNT DATA

FREQUENCY
SCORE
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SOME ADDITIONAL IDEAS

• NON-NORMAL DISTRIBUTIONS
• POISSON AND COUNT DATA

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DISTRIBUTIONAL ISSUES

• CENSORED PART OF THE NORMAL (eg. LIKERT ITEMS)-
  SUMMING SHOULD CREATE NORMAL
• INDIVIDUAL ITEMS CAN BE ANALYZED AS CENSORED
  NORMAL SCORES
• OF INTEREST IN RELIABILITY AND VALIDITY STUDIES