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Scaling and Multiple Item Measures

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Likeability, pleasantness of food ... Generosity. Contrast Error. Selecting Items. Criteria. Face (logical) validity. Unidimensionality ... – PowerPoint PPT presentation

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Title: Scaling and Multiple Item Measures


1
Scaling and Multiple Item Measures
2
Levels of Measurement
  • Remember
  • nominal
  • ordinal
  • interval
  • ratio

3
Nominal
  • Number of CasesMode
  • Religious groups
  • Qualities

4
Ordinal
  • Median, percentiles
  • Likeability, pleasantness of food
  • For example, on a survey you might code
    Educational Attainment as 0less than H.S.
    1some H.S. 2H.S. degree 3some college
    4college degree 5post college. In this
    measure, higher numbers mean more education. But
    is distance from 0 to 1 same as 3 to 4? Of course
    not. The interval between values is not
    interpretable in an ordinal measure.

5
Interval
  • Mean, Standard Deviation, Correlation
  • Temperature, Calendar dates
  • In interval measurement the distance between
    attributes does have meaning. For example, when
    we measure temperature (in Fahrenheit), the
    distance from 30-40 is same as distance from
    70-80. The interval between values is
    interpretable. Because of this, it makes sense to
    compute an average of an interval variable, where
    it doesn't make sense to do so for ordinal
    scales. But note that in interval measurement
    ratios don't make any sense - 80 degrees is not
    twice as hot as 40 degrees (although the
    attribute value is twice as large).

6
Ratio
  • Weight is a ratio variable. In applied social
    research most "count" variables are ratio, for
    example, the number of clients in past six
    months. Why? Because you can have zero clients
    and because it is meaningful to say that "...we
    had twice as many clients in the past six months
    as we did in the previous six months."

7
Types of Scales
  • Graphic
  • Feeling thermometer
  • Itemized
  • extremely healthyhealthy..not healthy.
  • Comparative
  • As compared to others.how do you rate ???

8
Cautions
  • Halo bias
  • Overall positive/negative
  • Generosity
  • Contrast Error

9
Selecting Items
  • Criteria
  • Face (logical) validity
  • Unidimensionality
  • General or specific
  • Variance

10
Empirical Relationships
  • Established when respondents answers to a
    question help predict how they will answer other
    questions.
  • If two items are empirically related, we can
    argue that each reflects the same variable, and
    both can be included in the same index.
  • Bivariate relationships - relationships between
    2 variables.
  • Multivariate relationships - relationship
    between more than 2 variables.

11
Assign Scores for Responses
  • Two basic decisions
  • Decide the desirable range of the scores.
  • Decide whether to give each item equal weight or
    different weights.

12
Techniques of Scale Construction
  • Thurstone scales - judges determine the intensity
    of different indicators. Assumes people will
    agree with only one position on an attitude
    dimension and disagree with other items in either
    direction http//www.socialresearchmethods.net/kb/
    scalthur.htm
  • .
  • Bogardus social distance scale - measures the
    willingness of people to participate in social
    relationshttp//gwbweb.wustl.edu/CMHSR/measure/k19
    .html

13
Techniques of Scale Construction
  • Likert scaling - uses standardized response
    categories.
  • Semantic differential -asks respondents to rank
    answers between two extremes.
  • Guttman scaling - uses an empirical intensity
    structure (most common). http//www.socialresearch
    methods.net/kb/scalgutt.htm

14
Example of a Likert Scale
  • http//www.socialresearchmethods.net/kb/scallik.ht
    m

15
Scales and Screening
  • ASDS (Aspergers Syndrome Disorder Screen)
  • MSI-R (Marital Satifaction Inventory-R)
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