The Dance between Accuracy and Bias - of David A. Kenny

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The Dance between Accuracy and Bias - of David A. Kenny Powered By Docstoc
					Social Relations Model:
  Multiple Variables
         David A. Kenny
  Types of Variables in
     SRM Studies
• Dyadic variable
• Personality variable
 –Self variable
• Group variable
    Multiple Dyadic
      Variables
Bivariate Correlations
 4 at the individual level
 2 at the dyadic level
    Dyadic Variables
Individual-level Correlations
    Actor-Actor
    Actor-Partner
    Partner-Actor
    Partner-Partner
       Actor-Actor
       Correlation
If initially a person sees others as
  Extroverted, does that person
  still see others as extroverted
  after interacting with them?
Not really: r = .21
     Actor-Partner
      Correlation
If initially a person sees others as
  Extroverted, is that person seen
  as extroverted after interacting
  with him or her?
Maybe: r = .46
     Partner-Actor
      Correlation
If a person is initially seen by
  others as Extroverted, does that
  person see others as
  extroverted after interacting
  with them?
Not really: r = -.02
   Partner-Partner
     Correlation
If initially a person is seen by
  others as Extroverted, is that
  seen as Extroverted after
  interacting with him or her?
Yes: r = .89
     Relationship
    Intrapersonal
    If one person, A, initially
thinks another person, B, is
particularly extroverted, does A
still think that B is particularly
extroverted after interacting
with him or her?
       Nor really: r = .23).
       Relationship
      Interpersonal
    If one person, A, initially
 thinks another person, B, is
 particularly extroverted, does B
 think that A is particularly
 extroverted after interacting
 with him or her?
Not really: r = -.15
Creating a Construct
Why?
    to separate error from
 relationship variance
  Multiple Measures
Same measure at different times.
Different measures at the same
 time.
            How?
Sum or average the scores.
Create a construct or a latent
 variable.
    Stable versus
  Unstable Variance
stable variance: variance that
  correlates across different
  measures of the construct
unstable variance: variance that
  is unique to the specific
  measure of the construct
Measurement Model
Equal loadings of the different
 measures: All measures need to
 have the same units.
Equal unstable variance in each
 measure
 Construct Variances
Stable Actor
Unstable Actor
Stable Partner
Unstable Partner
Stable Relationship
Unstable Relationship
      Error Variance
Very often Unstable Actor and
 Partner variances are very small.
There is only Unstable Relationship
 variance.
Can report error variance as the sum
 of Unstable Actor, Partner, and
 Relationship variances.
          Example
Liking at Two Times (Curry)
                 Stable Unstable
  Actor            .160     .029
  Partner          .259     .016
  Relationship     .422     .114
  Error                     .159
    Correlated Error
Some times, pairs of indicators share
 method variance.
    Same time
    Same instrument
Need to remove correlated error
 effect in computing correlations
 between two constructs.
A Personality
Variable with
  a Dyadic
  Variable
Extroversion (personality
 variable) with Smiling
    (dyadic variable)
Actor Personality Variable
 Correlation: If Dave is extroverted,
 does Dave smile more?
Partner Personality Variable
 Correlation: If Dave is extroverted,
 do others smile more at Dave?
A Personality Variable at
 the Relationship Level
Compute the product of actor’s
 personality X partner’s
 personality (both centered) or
 alternatively the absolute
 difference.
Correlate with relationship effect.
    Self Variable as a
   Special Personality
         Variable
Self Variable: A “dyadic”
 measurement in which actor
 and partner are the same
 person.
Can correlated with actor and
 partner effects.
      Group Variable
Same score for all group
 members.
Examples
 gender
 experimental condition
Tests
 level
 variances
  Suggested Readings
   Dyadic Data Analysis, Kenny,
Kashy, & Cook, Chapter 8
    Appendix B in Kenny’s
Interpersonal Perception (1994)
Thank You!

				
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posted:4/24/2014
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