Measurement, analysis, and sharing


          Daniel Messinger, Ph.D.
           University of Miami


           September 15, 2011
   From openshapa to open data sharing
Overview
            Problem: Lack of sharing
   Continuous measurement
       Objective—automated
       Subjective
       Analysis tools
   Categorical measurement
       Analysis tools
     Solution? Share behavioral databases…
                         http://measurement.psy.miami.edu/
Measurement problems
plague the behavioral sciences

 Investigator-specific systems

   Each lab re-invents the wheel
         in its own image
      hampering replication

         http://measurement.psy.miami.edu/
Broader systems have emerged
   Facial Action Coding System (FACS)
Require substantial training & implementation




     Instantiate with automated
           measurement
              http://measurement.psy.miami.edu/
Computer Vision




  http://measurement.psy.miami.edu/
Parent-Infant Interaction
    Infant Smile, Mother Smile




        http://measurement.psy.miami.edu/
                                            Messinger, et al., 2009
Variability at Every Level

                            5
                            4




                                                                                                                       Dyad A
                            3
Facial Actions & Tickling




                            2
                            1
                            0


                                    .35              .50                 .36                        .21
                                0    10   20   30   40   50   60   70   80    90 100 110 120 130 140 150 160 170 180


                            5
                            4




                                                                                                                       Dyad B
                            3
                            2
                            1
                            0

                                    .47         .42                     .28                        .58

                                                               http://measurement.psy.miami.edu/
Tools for continuous data




       http://measurement.psy.miami.edu/
Tools for continuous data




       http://measurement.psy.miami.edu/
Rating Constructs Directly




      http://measurement.psy.miami.edu/
                                          Baker et al., 2010;
                                          Chow et al., 2010
Rationale
Human beings are
   expert at the
continuous, intutive
evaluation of others

 The wisdom of
crowds….aggregate
   independent
   observations
            http://measurement.psy.miami.edu/
Time-series                                                                                                                               Mean
                                                                                                            Object of Measurement: 11.10

                                                                                                                                                         Parent
                            140.00                                                                                                                       Infant


                            120.00




                            100.00
Emotional Valence Ratings




                             80.00




                             60.00




                             40.00




                             20.00




                              0.00


                                     .00   10.00   20.00   30.00   40.00   50.00   60.00   70.00   80.00   90.00 100.00 110.00 120.00 130.00 140.00 150.00 160.00 170.00 180.00

                                                                                                     Seconds




                                                                                                                                                              http://measurement.psy.miami.edu/
                                                                                                                                                                                                    Baker et al., 2010a
Data analysis tools
                                  (responsivity varies in time)
Interactive Influence




                                                      it                              it  1  2   0  i ,t 1    ,it 
                                                                                           1 0                             
                        Infant it  1 0 Parent it  i ,t 1                         i ,t 1        0  i ,t  2    0 
                                                                                                           
                                                              
                                                     Bit 
                                                                                      Bit   0 0
                                                                                                       1  Bi ,t 1   B ,it 
                                                                                                                               
                          Chow et al., 2010
                                                            http://measurement.psy.miami.edu/
                                                                                                                      Chow et al., 2010
Reliability with expert measurement




                                                                        Expert Family Conflict
                                                                                                 Non-Expert Family Conflict
Expert Sensitive Structuring




                                 Non-Expert Sensitivity

                                                          http://measurement.psy.miami.edu/
                                                                                                                       Baker et al., 2010b
http://measurement.psy.miami.edu/cms.phtml




              http://measurement.psy.miami.edu/
Coding tool


                                    Easy Interface

                                    Frame-by-frame
                                       procession

                                     User-defined
                                        codes

http://measurement.psy.miami.edu/
Categorical data enable
identification of patterns




       http://measurement.psy.miami.edu/
Finding Temporal Patterns




       http://measurement.psy.miami.edu/
                                           Yale et al., 1999;
                                           Yale et al., 2003
Document the existence of patterns
              Observed Behaviors
                             Gazes                    Gazes
    No Smiles Smiles          Away                   at Mom
               SM

                SM

            To Create Simulated Pattern

    Smile                 SM                        SM

    Gaze

                Time
                psy.miami.edu/faculty/dmessinger/
Finding Temporal Patterns in Data

                     Smile                         SM            SM
Observed Pattern                            Smile in Gaze!

                     Gaze
                                                      Subtract

                     Smile                           SM          SM
  Simulated
Random Pattern
                     Gaze
Repeat 2000 times.                         Time

          Z = (Observed – Simulated)/SDS
                       psy.miami.edu/faculty/dmessinger/
The problem:
Studying a common phenomenon…
 Neonatal imitation                                     or not…

     Meltzoff



                 Google search…. macaques




                    http://measurement.psy.miami.edu/
Sharing Behavioral Data




      http://measurement.psy.miami.edu/
Automated measurement is
  collaborative research
                                    The Computer Expression
                                      Recognition Toolbox
                              http://mplab.ucsd.edu/~marni/Pro
                                       jects/CERT.htm




                                  http://www.pitt.edu/~jeffcohn/

                           http://www.ri.cmu.edu/research_lab_group
                             _detail.html?lab_id=51&menu_id=263



 Commercial software…http://www.noldus.com/news/new-facereader-30
                 http://measurement.psy.miami.edu/
Computer vision models




      http://measurement.psy.miami.edu/
The IRB issue…




Surmountable…
  http://measurement.psy.miami.edu/
Thanks!




Mohammad Mahoor, Lisa Ibanez, Jeffrey
  Cohn, Alan Fogel, & Sy-Miin Chow
    http://measurement.psy.miami.edu/

Messinger.openshapa.091511

  • 1.
    Measurement, analysis, andsharing Daniel Messinger, Ph.D. University of Miami September 15, 2011 From openshapa to open data sharing
  • 2.
    Overview Problem: Lack of sharing  Continuous measurement  Objective—automated  Subjective  Analysis tools  Categorical measurement  Analysis tools Solution? Share behavioral databases… http://measurement.psy.miami.edu/
  • 3.
    Measurement problems plague thebehavioral sciences Investigator-specific systems Each lab re-invents the wheel in its own image hampering replication http://measurement.psy.miami.edu/
  • 4.
    Broader systems haveemerged Facial Action Coding System (FACS) Require substantial training & implementation Instantiate with automated measurement http://measurement.psy.miami.edu/
  • 5.
    Computer Vision http://measurement.psy.miami.edu/
  • 6.
    Parent-Infant Interaction Infant Smile, Mother Smile http://measurement.psy.miami.edu/ Messinger, et al., 2009
  • 7.
    Variability at EveryLevel 5 4 Dyad A 3 Facial Actions & Tickling 2 1 0 .35 .50 .36 .21 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 5 4 Dyad B 3 2 1 0 .47 .42 .28 .58 http://measurement.psy.miami.edu/
  • 8.
    Tools for continuousdata http://measurement.psy.miami.edu/
  • 9.
    Tools for continuousdata http://measurement.psy.miami.edu/
  • 10.
    Rating Constructs Directly http://measurement.psy.miami.edu/ Baker et al., 2010; Chow et al., 2010
  • 11.
    Rationale Human beings are expert at the continuous, intutive evaluation of others The wisdom of crowds….aggregate independent observations http://measurement.psy.miami.edu/
  • 12.
    Time-series Mean Object of Measurement: 11.10 Parent 140.00 Infant 120.00 100.00 Emotional Valence Ratings 80.00 60.00 40.00 20.00 0.00 .00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00 110.00 120.00 130.00 140.00 150.00 160.00 170.00 180.00 Seconds http://measurement.psy.miami.edu/ Baker et al., 2010a
  • 13.
    Data analysis tools (responsivity varies in time) Interactive Influence   it    it  1  2 0  i ,t 1    ,it      1 0     Infant it  1 0 Parent it  i ,t 1   i ,t 1   0  i ,t  2    0      Bit     Bit   0 0    1  Bi ,t 1   B ,it      Chow et al., 2010 http://measurement.psy.miami.edu/ Chow et al., 2010
  • 14.
    Reliability with expertmeasurement Expert Family Conflict Non-Expert Family Conflict Expert Sensitive Structuring Non-Expert Sensitivity http://measurement.psy.miami.edu/ Baker et al., 2010b
  • 15.
    http://measurement.psy.miami.edu/cms.phtml http://measurement.psy.miami.edu/
  • 16.
    Coding tool Easy Interface Frame-by-frame procession User-defined codes http://measurement.psy.miami.edu/
  • 17.
    Categorical data enable identificationof patterns http://measurement.psy.miami.edu/
  • 18.
    Finding Temporal Patterns http://measurement.psy.miami.edu/ Yale et al., 1999; Yale et al., 2003
  • 19.
    Document the existenceof patterns Observed Behaviors Gazes Gazes No Smiles Smiles Away at Mom SM SM To Create Simulated Pattern Smile SM SM Gaze Time psy.miami.edu/faculty/dmessinger/
  • 20.
    Finding Temporal Patternsin Data Smile SM SM Observed Pattern Smile in Gaze! Gaze Subtract Smile SM SM Simulated Random Pattern Gaze Repeat 2000 times. Time Z = (Observed – Simulated)/SDS psy.miami.edu/faculty/dmessinger/
  • 21.
    The problem: Studying acommon phenomenon… Neonatal imitation or not…  Meltzoff Google search…. macaques http://measurement.psy.miami.edu/
  • 22.
    Sharing Behavioral Data http://measurement.psy.miami.edu/
  • 23.
    Automated measurement is collaborative research The Computer Expression Recognition Toolbox http://mplab.ucsd.edu/~marni/Pro jects/CERT.htm http://www.pitt.edu/~jeffcohn/ http://www.ri.cmu.edu/research_lab_group _detail.html?lab_id=51&menu_id=263 Commercial software…http://www.noldus.com/news/new-facereader-30 http://measurement.psy.miami.edu/
  • 24.
    Computer vision models http://measurement.psy.miami.edu/
  • 25.
    The IRB issue… Surmountable… http://measurement.psy.miami.edu/
  • 26.
    Thanks! Mohammad Mahoor, LisaIbanez, Jeffrey Cohn, Alan Fogel, & Sy-Miin Chow http://measurement.psy.miami.edu/