Feedback Experiment V32 by 25r4r3

VIEWS: 6 PAGES: 87

									                      Experimenter: Enter condition below, press Enter,
                              note instructions, and click RUN
                                                           Embedded instructions?
                                      Condition                    No
                                          6G
                                     Instructions                     Task
                                          1A                         UConn
                                                                                                      You can double cl
                              Code RLBHVEFF                                                           case presentation
If you choose to     Choose option for                                                                program.
email results, the   decision making
program will open       procedure
your default email
program and
generate a                               New        Bonus feedback (New or Old)
message to Tom
Stewart with the                          No        Email data (Yes or No)?
data attached.
                                                    Machine number automatically read from
                                        TestPC      ComputerID.xls



                                                         Run


                              Delete Output           Use this button to delete output after a test
                                                      run. Caution: It will delete all output on
                                                      the file. It will copy a new
                                                      FeedbackExperimentOutput.xls from a
                                                      directory named "Backup Files".



                        Yes          Startup value of judgment-before-decision control



                        For task choice on Intro sheet
                        Albany
                        UConn
                        ESB19

                        For bonus feedback
                        New
                        Old

                        For Yes/No
                        Yes
                        No
For testing
      Yes Skip MCPL instructions (disabled)
      Yes Skip MCPL cases
       No Skip Decision instructions
       No Skip Decision cases
       No Skip Final questions


You can double click on the word "Set" in
case presentation to restart or end
program.


 Conditions, reduced feedback
 proportions, instructions are all now
 determined by the Condition Table
 worksheet
For testing purposes, set number of cases and blocks below
            Number of blocks for MCPL (max 3)

            Cases presented per block for MCPL (max 25)*
        20 Number of blocks for decision task (max 20)
        25 Cases presented per block for decision task (max 25)

*Note that you won't get weight feedback for fewer than 25 MCPL cases.
  Why is the mean higher for RM, and does it matter? I don't think it matters
  Implement embedded instructions for UConn
  Randomize case presentation within block, but record output in constant order.




   Put all variable instructions in forms so we need           Add a button to delete output file when testing
   only one set of paper instructions.



   Reorganize output file so it produces more statistics and combines output in a
   format that is easier to input to SPSS.
                                                                                             Use Wbprotect and Elise
                                                                                             Subjects.
Change start and stop time storage to Output so that block names are not needed


 Implement uncertainty conditions




                                                                                           On subjective report form
 Add all new forms (to disable X on forms): (Done on all forms I know of)                  clear the text box if subjec
                                                                                           weight that is out of range
 Private Sub UserForm_QueryClose(Cancel As Integer, CloseMode As Integer)                  resetting is detected as ch
 'Stop a user from closing a UserForm via the X:                                           message is displayed.) In
 'http://www.ozgrid.com/VBA/MiscVBA.htm                                                    button is disabled until da
    If CloseMode = 0 Then
       Cancel = True                                                                       I disabled all checking on
       MsgBox "The X in the upper right corner has been disabled", vbCritical              weights because of a prob
    End If                                                                                 locking up due to type mis
 End Sub                                                                                   the problem
elete output file when testing




            Use Wbprotect and Elise's "Visuals" to hide all worksheet operations from
            Subjects.




           On subjective report form, text box, it should
           clear the text box if subject enters a subjective
           weight that is out of range. (I tried, but couldn't
           resetting is detected as change and then error
           message is displayed.) In version 16, the Next
           button is disabled until data are entered.

           I disabled all checking on the subjective
           weights because of a problem with machine
           locking up due to type mismatch. This solved
           the problem
Version
V10




V11


V12




V13


V13a

V14
V15




V16




V17


V17a
V18




V19
V20




V21




V22




V23
V24




V24a

V25




V26




V27

V27a

V27b




V28




V29
V30

V30a




V31




V30p

V30-2


V32


Next version to do
Added form for displaying cognitive feedback
Added email capability using routing slip
Added machine number and version number to output worksheet
Increased rows for ID's on Output workbook to 10.
Tested and improved Reduced feedback algorithm (see ReducedFBAlgorithmTest.xls
Reduced FB algorithm now spans 3 blocks
Added code to disable X close icon on forms
Added blank worksheets to Task and Output files
Added code to activate blank spreadsheets for background
Added code to make worksheets invisible, but I think that is not necessary
Revised instructions
Major failure prior to DAPS meeting. Eventually ran file through Office 97 maching and saved it. That seemed to
correct the problem
Change to customs officer task
Added condition code to welcome sheet. Preparing for using printed instructions.
Revised MCPL case presentation
Revised decision case presentation
Revised cue help
Revised decision scoring reminder
Revised subjective report questions for only decision cases
Revised output file to accept data from new subjective report form
Increased Decision blocks to 10 (many ranges have to be named on Experiment, Output, and Task data books
Added stopping rule and bonus payment calculation
Restored question about cutoff when we decided to force judgments before decisions
Cases and blocks can be easily changed
Defined worksheet objects
Generally cleaned up program - no changes from V12 should be visible to user
Corrected some problems with version 13
Replaced Excel 2000 Round function with old Worksheet function that will work in Excel 97
Change performance cutoff to 1750 based on simulations with new decision task data (20 blocks)
Correct error that caused score to be displayed wrong if subject stopped due to meeting performance standard
Removed all need to change program when program version changes
Adjusted forms that show points to work with 5 digits scores
Tested cue and decision display for 20 blocks. Seems ok. I did only one case per block.
Added storage of score and pctcorrect by block
Performance criterion was tested based on total score. I corrected to base it on block score.
This was used for group test on 9-30-05. Stopping threshold was set high so everyone had to do 20 blocks
Requires ComputerID.xls file with computer number in cell A1 of sheet1. Don't enter computer number on Intro
sheet.
Subject number is now automatically assigned as Year-Month-Day-Hour-Minute-MachineMachineNumber

The proportion of feedback in reduced feedback (Condition 1C) is now controlled by the
"ProportionPositive" cell (B4) on the Parameters sheet. This should be set equal to the mean proportion
of positive decisions made by the subjects in the partial feedback (1B) condition. NEEDS TESTING
First version used for actual experiment. Messages to testers removed
Perfomance cutoff disabled by setting at 2500 per block. "Good score" set at 2000 per block. This determines
the dollars per point.
Commented out the code on frmSubjectReport Weight text boxes that was meant to reject out of range entries.
We have been having problems with crashing when some (unknown) data was entered on that text box. Hope
this fixes it
Added "On Error Resume Next" to further try to prevent crashing when text is entered.
Subject number is now assigned after subject presses begin, rather than when the program starts. This makes
the time that is part of the subject number represent the actual start time, rather than the time the program was
started.
Corrected an error in clearing decision data from previous subject. 18 responses from block 20 were not cleared.
This inflated the scores up to block 20, and then gave a very small score for block 20 as the uncleared responses
were overwritten. We should delete the first 6 subjects.
Set up ProportionPositive = .5, based on average proportion of positive decisions by 12 people in the Partial
Feedback condition (.508). Also corrected program so this actually works. Reduced feedback changes
described above for version 16 got lost somewhere.
Enabled OK button for demographics and subjective report. Subjects do not have to enter anything on these
pages.
Added code so that program will start if TaskData and Ouput workbooks are already open.
Implemented base rate conditions
11/14/2005
Now runs Albany or UConn task (UConn is casereduced feedback condition.exactly this way onafter running
Enabled different proportion feedback cases for sensitive. Must be entered This must be set Intro sheet)
subjects in the corresponding Partial feedback condition and computing the mean number of Yes decisions
made.
This version requires the judgment slider to be moved before OK button is enabled.
11/20/2005
This provides for a new calculation of the bonus, taking into account the accuracy of judgment.
External bar gifs no longer needed. Bar images are stored on a form internally
Some unused forms deleted and stored.
MCPL now works with UConn task
TaskData file no longer needs to have data in every block named. Additional data for MCPL and decision can be
added without naming blocks -- however, the time data output may need to be revised if blocks are added.
2/1/2006
Computer ID is now part of name of output file. The file named FeedbackExperimentOutputTestPC.xls must be
in the same directory as this file. The name will be changed the first time the program is run.
Implemented the different payoff conditions. They are controlled by the "Values" sheet
Removed the table of conditions from the Intro sheet. It was becoming too large as additional conditions were
added. It also might become confusing having the properties of conditions stored in two different places. All the
controls for conditons are now on the "Condition Table" worksheet. The range is named "ConditionCodeTable."
Added column to Conditon Table so that UConn can use different base rates.
Table added to "Parameters" sheet converts base rates to thresholds. Thresholds must be determined manually.
If you try to use a base rate that is not in this table, you will get an error message and the program will terminate.
Changed condition table to use low base rate for experiment 3. Previously we had planned to use moderate
base rate, but that seems too easy.
Corrected the page number on page 2 of the subjective report.
Added validation so incorrect conditions cannot be entered. Also condition can be optionally chosen from drop
down list.
Added code to check status of condition and display status if present. Stops program to prevent attempts to run
invalid conditions.
Values for the VN and VP conditions were changed.
2/8/2006
Only formatting changes were made so that the program will look ok on the screens at the CIFA lab (ESB19).
TaskID's "Albany" and "Uconn" run on XGA (1024x778) 96 DPI.
"ESB19" TaskID runs on 1400x1050, 120 DPI screen. This is the same task as "Albany" but the forms are set to
cover the larger screen.
It should be possible to set up scaling for all screen sizes, but I haven't done that.
Versions 22 and later were created with Excel 2003. In order to run them on Excel 97, the program must be
compiled on a machine running Excel 97:
   1. Press Alt-F11 to open the Visual Basic window.
   2. Click Debug/Compile VBAProject.
   3. Pres Alt-Q to close and return to Excel.
   4. Save the Excel file.
2/24/2006
An extra column was added to the condition table recognizing that UConn is going to have different proportions
for reduced feedback. If task ID is "Uconn," the proportion is read from this column
Anyone in condition 2C prior to this version did not receive any feedback.
People in condition 1C at UConn received feedback based on a proportion of .5, which was based on Albany
subjects. will now terminateshould have aattempt to run.35
Program UConn subjects if there is an proportion of a reduced feedback condition when the proportion
positive is 0.
3-27-06 One subject actually met the vestigial 2500 point performance cutoff on two blocks. I have raised it to
3000 so this will not happen. If the performance cutoff is implemented in the future, frmStopDecisionTask will
have to be modified so it will work.
5/6/2006
This version will run from a flash drive (changes made to file names because ChDir will not change drives.
5/8/2006
Added a cell on the intro sheet to indicate use of USB drive. Entering Yes will cause output after each block to be
backed up on the c drive instead of the USBdrive, eliminating delays due to slow writing on USB drive. The
backup file is c:/My Documents/FeedbackOutputBackup.xls . It is deleted after the output is saved to the flash
drive.
This works for the computers set up in Draper 023. It may not work on other computers. For Tom Stewart's
laptop, for example, another method, involving "environ," is needed. This method is commented out in the code.
Useful website for finding the My Documents directory:
http://blogs.officezealot.com/charles/archive/2004/12/10/3574.aspx
Useful website for file operations:
http://www.exceltip.com/st/Basic_file_and_folder_examples_using_VBA_in_Microsoft_Excel/443.html
Started 5-9-2006
Adding error handling to Case presentation. Displays error message, creates error log, provides restarting
options. This has not been tested on a real error.
This version sets calculation to automatic. Program will not run if calculation is not automatic.
Enabled double click on "Set" label to provide restart options (same as error options).
Added button to delete output file after testing.
6/14/2006
Activates the reduced feedback conditions for Albany based on data gathered up to 6/13/06
6/23/2006
Does not save temporary output after each block
6/23/2006
Some minor changes related to the removal of saving the temporary backup output file
On 8-28 I disabled the command that turns autocalcualtion on because it does not work on Excel 97 computers in
Milne 323. Users should manually check to make sure autocalculation is on, or enable the command if they are
running Excel 2003
10/5/2006
Implements low and high uncertainty conditions (RL and RH) - Requires task data version 5
Reduced FB for experiment 4 not yet implemented. Need to run partial feedback first.
Eliminates blank row between blocks that were causing problems
Checks to make sure task data file has been updated to version 5
10/16/2006
Provides option for embedded instructions for Albany and UConn
          11/7/06, changed properties on Close button for scoring feedback to try to make it work on Jim's machine.
          11/22/2006
          Implemented partial feedback conditions for Experiment 4-UConn.
          1/25/2007 (Demo version. Demo capability is not included in subsequent versions)
          For Jeryl's 611 class, I wanted to not require judgments, but this caused some problems, which have now been
          fixed. The feedback screens still refer to judgment. They will have to be changed if the no judgment case is used
          in research.
          Added a "Demo" condition on the condition table. The conditions can be set for specific demos.
          Attempted to make restart options available on the final screen if want to cut off demo early. Did not work, and
          would require a lot of work to implement. Best to start the next block and then terminate.
          1/26/2007 (Demo version. Demo capability is not included in subsequent versions)
          This version implements "DEMO" capability so the program can be used as a stand alone for class exercises. Be
          careful with this because it hides all the spreadsheets and tries to prevent any user control of the program or
          spreadsheets. There is a "back door" available: double click on the intro label.
          This version does not include the capabilty for Experiment 5
          2/11/2007
          Implemented partial feedback conditions for Experiment 4, screening task (based on UConn subjects).
          4/9/2007
          Implemented experiment 5 - same as experiment 4, but with low base rate (.1)
          Condition Table changed to full/conditional/partial
          2/11/2008
          Implemented experiment 6 - same as experiment 4, but with high base rate (.8)

Next version to do
           Separate screen resolution from task ("ESB19") so either task can be run at either resolution.
Table of conditions
The row in this table will determine the parameters of the program for each subject in each condition.

                                                                 Condition Code




                                                                                                                                                                                                                                              Feedback (full, partial, and
                                                                                                                                                                        UConn base rate (Task =
                                                                                                                                             Albany base rate (Task =
                                                                                                                  Uncertainty (.5, .7, .9)
                                                                                Value Structure
                                            Instructions




                                                                   Base Rate
                                                                                                                                                                                                                                                                              Reduced Reduced                                                            Status (program




                                                                                                       Feedback




                                                                                                                                                                              "UConn")
                                                                                                                                                    "Albany")




                                                                                                                                                                                                                                                     reduced)
                                                                                                                                                                                                     Value structure (Equal penalty,
                                                                                                                                                                                                                                                                              feedback feedback                                                           will not run for




                                                            R2
                Description                                                                                                                                                                        greater penalty for false positives,                                                                                   Experiment                                                     Notes
                                                                                                                                                                                                                                                                             proportion- proportion-                                                     condition if this is
                                                                                                                                                                                                   greater penalty for false negatives)
                                                                                                                                                                                                                                                                               Albany      UConn                                                           NOT blank)




1A     Base case                        1A                 RM    BM            VE                 FF              0.7                           0.5                        0.5                    Equal                                   Full                                                        Experiment I, main effect for feedback
1B     Base case                        1B                 RM    BM            VE                 FP              0.7                           0.5                        0.5                    Equal                                   Conditional                                                 Experiment I, main effect for feedback
1C     Base case                        1C                 RM    BM            VE                 FR              0.7                           0.5                        0.5                    Equal                                   Partial                                   0.5          0.35 Experiment I, main effect for feedback                                    11 people at Uconn were run with the Albany proportion of .5
2A     Base case                        1A                 RM    BM            VE                 FF              0.7                           0.5                        0.5                    Equal                                   Full                                                        Experiment II – base rate x feedback
2B     Base case                        1B                 RM    BM            VE                 FP              0.7                           0.5                        0.5                    Equal                                   Conditional                                                 Experiment II – base rate x feedback
2C     Base case                        1C                 RM    BM            VE                 FR              0.7                           0.5                        0.5                    Equal                                   Partial                                   0.5          0.35 Experiment II – base rate x feedback                                      12 people at Uconn were run before the proportion was set
2D     Low base rate                    1A                 RM    BL            VE                 FF              0.7                           0.1                        0.1                    Equal                                   Full                                                        Experiment II – base rate x feedback
2E     Low base rate                    1B                 RM    BL            VE                 FP              0.7                           0.1                        0.1                    Equal                                   Conditional                                                 Experiment II – base rate x feedback
2F     Low base rate                    1C                 RM    BL            VE                 FR              0.7                           0.1                        0.1                    Equal                                   Partial                                  0.15          0.15 Experiment II – base rate x feedback
2G     High base rate                   1A                 RM    BH            VE                 FF              0.7                           0.8                        0.8                    Equal                                   Full                                                        Experiment II – base rate x feedback
2H     High base rate                   1B                 RM    BH            VE                 FP              0.7                           0.8                        0.8                    Equal                                   Conditional                                                 Experiment II – base rate x feedback
2I     High base rate                   1C                 RM    BH            VE                 FR              0.7                           0.8                        0.8                    Equal                                   Partial                                  0.66          0.66 Experiment II – base rate x feedback
3A     Albany-Same as 2D                1A                 RM    BL            VE                 FF              0.7                           0.1                        0.2                    Equal                                   Full                                                        Experiment III –payoff x feedback
3B     Albany-Same as 2E                1B                 RM    BL            VE                 FP              0.7                           0.1                        0.2                    Equal                                   Conditional                                                 Experiment III –payoff x feedback
3C     Albany-Same as 2F                1C                 RM    BL            VE                 FR              0.7                           0.1                        0.2                    Equal                                   Partial                              0.15781           0.16 Experiment III –payoff x feedback
3D     Penalize false negatives         3D                 RM    BL            VN                 FF              0.7                           0.1                        0.2                    Greater penalty for false negatives     Full                                                        Experiment III –payoff x feedback
3E     Penalize false negatives         3E                 RM    BL            VN                 FP              0.7                           0.1                        0.2                    Greater penalty for false negatives     Conditional                                                 Experiment III –payoff x feedback
3F     Penalize false negatives         3F                 RM    BL            VN                 FR              0.7                           0.1                        0.2                    Greater penalty for false negatives     Partial                             0.222095           0.21 Experiment III –payoff x feedback
3G     Penalize false positives         3G                 RM    BL            VP                 FF              0.7                           0.1                        0.2                    Greater penalty for false positives     Full                                                        Experiment III –payoff x feedback
3H     Penalize false positives         3H                 RM    BL            VP                 FP              0.7                           0.1                        0.2                    Greater penalty for false positives     Conditional                                                 Experiment III –payoff x feedback
3I     Penalize false positives         3I                 RM    BL            VP                 FR              0.7                           0.1                        0.2                    Greater penalty for false positives     Partial                             0.130857           0.19 Experiment III –payoff x feedback
4A     Base case                        1A                 RM    BM            VE                 FF              0.7                           0.5                        0.5                    Equal                                   Full                                                        Experiment IV – uncertainty x feedback
4B     Base case                        1B                 RM    BM            VE                 FP              0.7                           0.5                        0.5                    Equal                                   Conditional                                                 Experiment IV – uncertainty x feedback
4C     Base case                        1C                 RM    BM            VE                 FR              0.7                           0.5                        0.5                    Equal                                   Partial                                                     Experiment IV – uncertainty x feedback             Reduced feedback not implemented. Choose another condition
4D     Less uncertainty                 1A                 RH    BM            VE                 FF              0.9                           0.5                        0.5                    Equal                                   Full                                                        Experiment IV – uncertainty x feedback
4E     Less uncertainty                 1B                 RH    BM            VE                 FP              0.9                           0.5                        0.5                    Equal                                   Conditional                                                 Experiment IV – uncertainty x feedback
4F     Less uncertainty                 1C                 RH    BM            VE                 FR              0.9                           0.5                        0.5                    Equal                                   Partial                             0.484435    0.4643657 Experiment IV – uncertainty x feedback
4G     More uncertainty                 1A                 RL    BM            VE                 FF              0.5                           0.5                        0.5                    Equal                                   Full                                                        Experiment IV – uncertainty x feedback
4H     More uncertainty                 1B                 RL    BM            VE                 FP              0.5                           0.5                        0.5                    Equal                                   Conditional                                                 Experiment IV – uncertainty x feedback
4I     More uncertainty                 1C                 RL    BM            VE                 FR              0.5                           0.5                        0.5                    Equal                                   Partial                             0.482696        0.4197 Experiment IV – uncertainty x feedback
5A     Base case                        1A                 RM    BL            VE                 FF              0.7                           0.1                        0.1                    Equal                                   Full                                                         Experiment 5 – uncertainty x feedback - low BR
5B     Base case                        1B                 RM    BL            VE                 FP              0.7                           0.1                        0.1                    Equal                                   Conditional                                                  Experiment 5 – uncertainty x feedback - low BR
5C     Base case                        1C                 RM    BL            VE                 FR              0.7                           0.1                        0.1                    Equal                                   Partial                                                      Experiment 5 – uncertainty x feedback - low BR    Reduced feedback not implemented. Choose another condition
5D     Less uncertainty                 1A                 RH    BL            VE                 FF              0.9                           0.1                        0.1                    Equal                                   Full                                                         Experiment 5 – uncertainty x feedback - low BR
5E     Less uncertainty                 1B                 RH    BL            VE                 FP              0.9                           0.1                        0.1                    Equal                                   Conditional                                                  Experiment 5 – uncertainty x feedback - low BR
5F     Less uncertainty                 1C                 RH    BL            VE                 FR              0.9                           0.1                        0.1                    Equal                                   Partial                                                      Experiment 5 – uncertainty x feedback - low BR    Reduced feedback not implemented. Choose another condition
5G     More uncertainty                 1A                 RL    BL            VE                 FF              0.5                           0.1                        0.1                    Equal                                   Full                                                         Experiment 5 – uncertainty x feedback - low BR
5H     More uncertainty                 1B                 RL    BL            VE                 FP              0.5                           0.1                        0.1                    Equal                                   Conditional                                                  Experiment 5 – uncertainty x feedback - low BR
5I     More uncertainty                 1C                 RL    BL            VE                 FR              0.5                           0.1                        0.1                    Equal                                   Partial                                                      Experiment 5 – uncertainty x feedback - low BR    Reduced feedback not implemented. Choose another condition
6A     Base case                        1A                 RM    BH            VE                 FF              0.7                           0.8                        0.8                    Equal                                   Full                                                         Experiment 6 – uncertainty x feedback - high BR
6B     Base case                        1B                 RM    BH            VE                 FP              0.7                           0.8                        0.8                    Equal                                   Conditional                                                  Experiment 6 – uncertainty x feedback - high BR
6C     Base case                        1C                 RM    BH            VE                 FR              0.7                           0.8                        0.8                    Equal                                   Partial                                                      Experiment 6 – uncertainty x feedback - high BR   Reduced feedback not implemented. Choose another condition
6D     Less uncertainty                 1A                 RH    BH            VE                 FF              0.9                           0.8                        0.8                    Equal                                   Full                                                         Experiment 6 – uncertainty x feedback - high BR
6E     Less uncertainty                 1B                 RH    BH            VE                 FP              0.9                           0.8                        0.8                    Equal                                   Conditional                                                  Experiment 6 – uncertainty x feedback - high BR
6F     Less uncertainty                 1C                 RH    BH            VE                 FR              0.9                           0.8                        0.8                    Equal                                   Partial                                                      Experiment 6 – uncertainty x feedback - high BR   Reduced feedback not implemented. Choose another condition
6G     More uncertainty                 1A                 RL    BH            VE                 FF              0.5                           0.8                        0.8                    Equal                                   Full                                                         Experiment 6 – uncertainty x feedback - high BR
6H     More uncertainty                 1B                 RL    BH            VE                 FP              0.5                           0.8                        0.8                    Equal                                   Conditional                                                  Experiment 6 – uncertainty x feedback - high BR
6I     More uncertainty                 1C                 RL    BH            VE                 FR              0.5                           0.8                        0.8                    Equal                                   Partial                                                      Experiment 6 – uncertainty x feedback - high BR   Reduced feedback not implemented. Choose another condition

       Greyed out conditions are not yet implemented in this program
            Various parameters are set here.
             Value          Name                 Purpose
                        0   ProportionPositive   Proportion of positive decisions for people in partial feedback. Controls proport
                       6G   CurrentCondition
                       25   MaxCases             Sets the maximum number of cases for a block of MCPL learning trials. This sh
Colored
                        0   ShowCases            Set the number of cases presented in MCPL learning.
cells are
                        3   NumCues              Sets the number of cues (Note - if you change this, other changes are required
set on
Intro                   0   MaxBlocks            Sets the number of MCPL learning blocks presented
page
                      20 MaxBlocksDecision Sets the number of decision learning blocks
                      25 MaxCasesDecision Sets the maximum number of cases for a block of decision trials. This should r
                      25 ShowCasesDecision Set the number of cases presented in decision making'
               20.0      CueWtIdeal01         Ideal cue weight for Cue 1
               50.0      CueWtIdeal02         Ideal cue weight for Cue 2
               30.0      CueWtIdeal03         Ideal cue weight for Cue 3
             Clothing CueName01               Name for cue 1
           Emotionality CueName02             Name for cue 2
             Bulging     CueName03            Name for cue 3
       Emotional maturityCueNameUConn01 Name for cue 1
                         CueNameUConn02 Name for cue 2
        Attention to detail
                         CueNameUConn03 Name for cue 3
        Interpersonal skill
                                                             Threshold for uncert. cond.
                                              Base Rate      RM            RL          RH
                                                 0.100      7.860        7.000        7.608 BL
                       Table for converting
                       base rates to             0.200      7.240        6.396        6.736 BL
                       thresholds. Only          0.500      5.640        5.012        5.204 BM
                       base rates listed here    0.800      4.300        3.569        3.652 BH
                       will work properly.                                                    Put future base rates here, sort t
                                                                                              Put future base rates here, sort t
                                                                                              Put future base rates here, sort t
Decision task Performance cutoffs
                        CutoffDollarsTable                         10 Dollars maximum bonus
                           Points required on             Exponent
                            two consecutive     Dollars      for
            Condition        blocks to quit    per point correlation
                1A                3000          0.00017        1       In the "New" performance bonus
                1B                3000          0.00017        1       system, the bonus is the number of
                1C                3000          0.00017        1       points X dollars per point X judgment
                2D                3000          0.00017        1       accuracy correlation.
                2E                3000          0.00017        1
                2F                3000          0.00017        1       The judgment accuracy correlation is the
                2G                3000          0.00017        1       correlation between the judgment and
                2H                3000          0.00017        1       the calculated Y using the ideal weights.
                2I                3000          0.00017        1       It is taken to a power determined by the
                3A                3000          0.00017        1       exponent.
                3B                3000          0.00017        1
                3C                3000          0.00017        1       To get the old performance bonus, set
                                                                       dollars per point to .00025 for all
                3D                3000          0.00017        1
                                                                       conditions and set the exponent to 0. If
                3E                3000          0.00017        1
                                                                       you use the old bonus, make sure to set
                3F                3000          0.00017        1       the feedback flag on the intro page to
                3G                3000          0.00017        1       get the feedback that only mentions the
                                                                       decision points.
                                                                       get the feedback that only mentions the
                   3H              3000           0.00017          1   decision points.
                   3I              3000           0.00017          1
                   4A              3000           0.00017          1
                   4B              3000           0.00017          1
                   4C              3000           0.00017          1
                   4D              3000           0.00017          1
                   4E              3000           0.00017          1
                   4F              3000           0.00017          1
                   4G              3000           0.00017          1
                   4H              3000           0.00017          1
                   4I              3000           0.00017          1
                   5A              3000           0.00017          1
                   5B              3000           0.00017          1
                   5C              3000           0.00017          1
                   5D              3000           0.00017          1
                   5E              3000           0.00017          1
                   5F              3000           0.00017          1
                   5G              3000           0.00017          1
                   5H              3000           0.00017          1
                   5I              3000           0.00017          1
                   6A              3000           0.00017          1
                   6B              3000           0.00017          1
                   6C              3000           0.00017          1
                   6D              3000           0.00017          1
                   6E              3000           0.00017          1
                   6F              3000           0.00017          1
                   6G              3000           0.00017          1
                   6H              3000           0.00017          1
                   6I              3000           0.00017          1
             Set these at 2500 to eliminate performance cutoff.
             1750 was used as a reasonable cutoff




          Various indicators of current status are stored below.
            Value          Name                 Purpose
                         1 CurrentBlock
                        VE Current Values condition (need to look up values on TaskDataDecision)


Original order and order
      for storage                               Presentation order
                                                Within
                                                block      Overall
                                                randomiza randomizat
Block       Case             Random numbers     tion       ion
        1                1        0.341868894           1          1
        1                4        0.462218468           4          2
        1               21        0.986538618          21          3
        1               16        0.944875174          16          4
        1                3        0.413197534           3          5
1   22   0.207936904    22    6
1    9   0.341496419     9    7
1   14    0.61633664    14    8
1   10   0.657305431    10    9
1    2   0.419745386     2   10
1   17   0.099259428    17   11
1   25   0.082628946    25   12
1   24   0.735131255    24   13
1   15    0.12189003    15   14
1   13   0.594197503    13   15
1   18   0.593025211    18   16
1    8   0.067349459     8   17
1   19   0.284282548    19   18
1   12    0.85765772    12   19
1    5   0.092633694     5   20
1   20   0.169490721    20   21
1    7   0.158088749     7   22
1   23   0.043788226    23   23
1    6    0.14377668     6   24
1   11   0.055894042    11   25
2    1   0.323365793     1   26
2    2    0.94324492     2   27
2    3      0.7024273    3   28
2    4   0.115722927     4   29
2    5   0.433692611     5   30
2    6   0.678992416     6   31
2    7   0.010332093     7   32
2    8   0.374608685     8   33
2    9   0.834338457     9   34
2   10   0.369131233    10   35
2   11   0.752089605    11   36
2   12   0.998186123    12   37
2   13   0.122756968    13   38
2   14   0.859157792    14   39
2   15   0.844928701    15   40
2   16   0.463247748    16   41
2   17   0.556644766    17   42
2   18   0.738932645    18   43
2   19   0.307803918    19   44
2   20   0.738390618    20   45
2   21   0.485617452    21   46
2   22   0.028885199    22   47
2   23   0.401437916    23   48
2   24   0.809256507    24   49
2   25    0.96065688    25   50
3    1   0.163622656     1   51
3    2   0.590835368     2   52
3    3   0.245910337     3   53
3    4      0.3142447    4   54
3    5   0.579746717     5   55
3    6   0.951158406     6   56
3    7   0.436571876     7   57
3    8   0.634309265    8    58
3    9   0.995483244    9    59
3   10   0.210091062   10    60
3   11   0.186109022   11    61
3   12   0.283353712   12    62
3   13    0.53519201   13    63
3   14   0.895343265   14    64
3   15   0.813471563   15    65
3   16   0.250080443   16    66
3   17   0.859404315   17    67
3   18   0.611353396   18    68
3   19   0.386792062   19    69
3   20   0.769490539   20    70
3   21   0.747749773   21    71
3   22   0.233437119   22    72
3   23   0.020365957   23    73
3   24   0.922878099   24    74
3   25   0.794605989   25    75
4    1   0.540842338    1    76
4    2   0.588882014    2    77
4    3   0.334817003    3    78
4    4    0.54870997    4    79
4    5   0.823162993    5    80
4    6    0.85747574    6    81
4    7   0.654720313    7    82
4    8   0.307206527    8    83
4    9   0.556067957    9    84
4   10   0.804317152   10    85
4   11   0.035197946   11    86
4   12   0.625294624   12    87
4   13   0.621422117   13    88
4   14   0.412215838   14    89
4   15   0.320271599   15    90
4   16   0.192985253   16    91
4   17   0.155714593   17    92
4   18   0.476336019   18    93
4   19   0.196706977   19    94
4   20   0.970542615   20    95
4   21   0.432743091   21    96
4   22   0.890622167   22    97
4   23   0.855848874   23    98
4   24    0.34601395   24    99
4   25   0.710227732   25   100
5    1    0.29730167    1   101
5    2    0.10208137    2   102
5    3   0.097189736    3   103
5    4   0.785185544    4   104
5    5   0.212862902    5   105
5    6   0.508028024    6   106
5    7   0.844740376    7   107
5    8   0.400027835    8   108
5    9   0.797641528    9   109
5   10   0.934736536    10   110
5   11    0.85425912    11   111
5   12    0.71029071    12   112
5   13   0.871546333    13   113
5   14   0.630899791    14   114
5   15      0.2510331   15   115
5   16   0.684629973    16   116
5   17   0.253907715    17   117
5   18   0.917349288    18   118
5   19   0.893293773    19   119
5   20   0.848324508    20   120
5   21   0.774017686    21   121
5   22   0.182700265    22   122
5   23   0.851215237    23   123
5   24    0.81446234    24   124
5   25   0.414521635    25   125
6    1   0.296924442     1   126
6    2   0.976730569     2   127
6    3   0.696172485     3   128
6    4   0.940730481     4   129
6    5   0.173847861     5   130
6    6   0.924333057     6   131
6    7   0.553821547     7   132
6    8   0.699628693     8   133
6    9   0.130864191     9   134
6   10   0.610336832    10   135
6   11   0.901918965    11   136
6   12   0.519936842    12   137
6   13   0.022380786    13   138
6   14   0.505153536    14   139
6   15   0.451496169    15   140
6   16   0.842286183    16   141
6   17   0.856003625    17   142
6   18    0.66776196    18   143
6   19   0.409264746    19   144
6   20   0.512535872    20   145
6   21   0.574974923    21   146
6   22   0.496366305    22   147
6   23   0.632696707    23   148
6   24   0.017823642    24   149
6   25    0.88038203    25   150
7    1   0.017138202     1   151
7    2   0.294811781     2   152
7    3    0.25529534     3   153
7    4   0.937237569     4   154
7    5   0.749504809     5   155
7    6   0.182052914     6   156
7    7   0.787475739     7   157
7    8   0.733726582     8   158
7    9   0.419729746     9   159
7   10   0.040241283    10   160
7   11   0.869256151    11   161
7   12   0.596333715   12   162
7   13   0.560958711   13   163
7   14    0.32689117   14   164
7   15   0.186235917   15   165
7   16   0.771475217   16   166
7   17   0.353282501   17   167
7   18   0.251862232   18   168
7   19   0.298550374   19   169
7   20    0.98470874   20   170
7   21   0.890776915   21   171
7   22   0.597522157   22   172
7   23   0.904152485   23   173
7   24   0.926354095   24   174
7   25   0.493357687   25   175
8    1   0.924521007    1   176
8    2   0.748553975    2   177
8    3   0.016696714    3   178
8    4   0.701437077    4   179
8    5   0.685735649    5   180
8    6   0.755833335    6   181
8    7   0.804225622    7   182
8    8   0.677780396    8   183
8    9   0.205092073    9   184
8   10   0.924863146   10   185
8   11   0.638636399   11   186
8   12   0.883624269   12   187
8   13   0.598597283   13   188
8   14   0.400666813   14   189
8   15   0.748001784   15   190
8   16   0.535134643   16   191
8   17   0.432978085   17   192
8   18    0.41501258   18   193
8   19   0.242682563   19   194
8   20   0.750411803   20   195
8   21   0.252675418   21   196
8   22   0.572695583   22   197
8   23   0.644582189   23   198
8   24   0.998580644   24   199
8   25   0.414262666   25   200
9    1   0.687663961    1   201
9    2   0.507235369    2   202
9    3   0.446994194    3   203
9    4   0.109955425    4   204
9    5   0.417222905    5   205
9    6   0.092420519    6   206
9    7   0.878139498    7   207
9    8   0.829355422    8   208
9    9   0.326453197    9   209
9   10   0.651335759   10   210
9   11   0.942003176   11   211
9   12   0.243949635   12   212
9   13    0.36198489   13   213
 9   14   0.158170425   14   214
 9   15   0.688590853   15   215
 9   16   0.943255477   16   216
 9   17    0.89098831   17   217
 9   18   0.999922952   18   218
 9   19   0.942161259   19   219
 9   20   0.462631792   20   220
 9   21   0.777231925   21   221
 9   22    0.32953895   22   222
 9   23   0.175133072   23   223
 9   24   0.190236912   24   224
 9   25   0.683995622   25   225
10    1   0.170694561    1   226
10    2    0.26340915    2   227
10    3   0.490589136    3   228
10    4   0.545992872    4   229
10    5   0.861501527    5   230
10    6   0.008257639    6   231
10    7   0.807162549    7   232
10    8   0.780085849    8   233
10    9   0.258331248    9   234
10   10    0.58798657   10   235
10   11    0.37719354   11   236
10   12   0.685854977   12   237
10   13   0.303481365   13   238
10   14   0.378789864   14   239
10   15   0.750754015   15   240
10   16   0.913311941   16   241
10   17   0.325115279   17   242
10   18   0.853413678   18   243
10   19   0.480621359   19   244
10   20    0.05799665   20   245
10   21   0.556319328   21   246
10   22   0.817614587   22   247
10   23    0.28245061   23   248
10   24   0.465585269   24   249
10   25   0.179173282   25   250
11    1   0.449631924    1   251
11    2   0.417318359    2   252
11    3   0.496499471    3   253
11    4   0.269644212    4   254
11    5   0.112035237    5   255
11    6   0.937871739    6   256
11    7   0.353242332    7   257
11    8   0.980917526    8   258
11    9   0.947454294    9   259
11   10   0.899416647   10   260
11   11    0.40792995   11   261
11   12   0.972047585   12   262
11   13   0.762793688   13   263
11   14   0.666580547   14   264
11   15   0.322304694   15   265
11   16   0.885443321   16   266
11   17   0.777701687   17   267
11   18   0.380099638   18   268
11   19   0.527277731   19   269
11   20   0.749059959   20   270
11   21   0.328968551   21   271
11   22   0.833404018   22   272
11   23   0.334249083   23   273
11   24   0.785338789   24   274
11   25   0.217948637   25   275
12    1   0.057560366    1   276
12    2   0.462431639    2   277
12    3   0.758839257    3   278
12    4   0.803469614    4   279
12    5   0.438733199    5   280
12    6   0.423152224    6   281
12    7   0.526201449    7   282
12    8    0.13488242    8   283
12    9   0.583968519    9   284
12   10   0.944323943   10   285
12   11   0.155327309   11   286
12   12   0.442341002   12   287
12   13   0.355623656   13   288
12   14   0.570573537   14   289
12   15   0.437803476   15   290
12   16   0.707259544   16   291
12   17   0.424823487   17   292
12   18   0.920681968   18   293
12   19   0.994003365   19   294
12   20   0.133652074   20   295
12   21   0.054761229   21   296
12   22    0.72496065   22   297
12   23   0.107547966   23   298
12   24   0.675293428   24   299
12   25   0.455292705   25   300
13    1   0.511798183    1   301
13    2   0.925774348    2   302
13    3   0.022887466    3   303
13    4   0.500094958    4   304
13    5   0.417237381    5   305
13    6   0.267038106    6   306
13    7   0.507487126    7   307
13    8   0.869732808    8   308
13    9   0.353575784    9   309
13   10   0.526007197   10   310
13   11   0.669606547   11   311
13   12   0.862271312   12   312
13   13   0.006738891   13   313
13   14   0.191796176   14   314
13   15   0.320560674   15   315
13   16   0.705712798   16   316
13   17   0.356557745   17   317
13   18   0.006720985   18   318
13   19   0.742413034   19   319
13   20   0.613336056   20   320
13   21   0.793867541   21   321
13   22   0.190282989   22   322
13   23   0.840353704   23   323
13   24   0.991158007   24   324
13   25   0.529840951   25   325
14    1   0.024962716    1   326
14    2   0.497284498    2   327
14    3   0.139900333    3   328
14    4   0.069778312    4   329
14    5   0.354678672    5   330
14    6   0.943105319    6   331
14    7   0.272806914    7   332
14    8   0.665695609    8   333
14    9   0.605073036    9   334
14   10   0.821499709   10   335
14   11   0.774819882   11   336
14   12   0.117562521   12   337
14   13   0.511216088   13   338
14   14   0.901761756   14   339
14   15   0.808158434   15   340
14   16   0.466058221   16   341
14   17   0.201257931   17   342
14   18   0.620853566   18   343
14   19   0.836275518   19   344
14   20   0.448946012   20   345
14   21   0.134007682   21   346
14   22   0.106476189   22   347
14   23   0.826593213   23   348
14   24   0.510003077   24   349
14   25   0.602040768   25   350
15    1   0.541877521    1   351
15    2   0.460492534    2   352
15    3   0.261867413    3   353
15    4   0.203213211    4   354
15    5   0.030103573    5   355
15    6   0.514523097    6   356
15    7    0.89868366    7   357
15    8   0.407042931    8   358
15    9   0.881618339    9   359
15   10   0.818581132   10   360
15   11   0.779363628   11   361
15   12   0.702377374   12   362
15   13   0.928013457   13   363
15   14   0.034207553   14   364
15   15   0.483207468   15   365
15   16   0.980736215   16   366
15   17   0.427349277   17   367
15   18   0.345203669   18   368
15   19   0.160202288   19   369
15   20    0.87083112   20   370
15   21    0.03175668   21   371
15   22   0.998175655   22   372
15   23   0.427418756   23   373
15   24   0.631706127   24   374
15   25   0.055714053   25   375
16    1   0.005403702    1   376
16    2   0.969092667    2   377
16    3    0.22960002    3   378
16    4   0.204090028    4   379
16    5   0.571141168    5   380
16    6    0.60256546    6   381
16    7   0.204397101    7   382
16    8   0.962197644    8   383
16    9   0.726548773    9   384
16   10    0.88513066   10   385
16   11   0.840778395   11   386
16   12   0.489673794   12   387
16   13   0.702305394   13   388
16   14   0.074887769   14   389
16   15   0.248031912   15   390
16   16   0.448126896   16   391
16   17   0.484538056   17   392
16   18   0.920200655   18   393
16   19   0.372696909   19   394
16   20   0.862428432   20   395
16   21    0.59350887   21   396
16   22   0.858504379   22   397
16   23   0.583034777   23   398
16   24   0.686602893   24   399
16   25   0.923611116   25   400
17    1   0.486673631    1   401
17    2   0.337899374    2   402
17    3   0.133565204    3   403
17    4   0.128948031    4   404
17    5    0.78256823    5   405
17    6   0.561822478    6   406
17    7   0.691419469    7   407
17    8   0.364990097    8   408
17    9   0.967782041    9   409
17   10   0.121507746   10   410
17   11   0.050093147   11   411
17   12   0.911191478   12   412
17   13   0.126744108   13   413
17   14   0.581010847   14   414
17   15   0.130892149   15   415
17   16   0.618229167   16   416
17   17   0.769545355   17   417
17   18   0.045153242   18   418
17   19   0.152954764   19   419
17   20   0.874755938   20   420
17   21   0.787691608   21   421
17   22   0.056352291    22   422
17   23   0.199192288    23   423
17   24    0.42244817    24   424
17   25   0.802030738    25   425
18    1   0.929768494     1   426
18    2   0.118478928     2   427
18    3   0.680770081     3   428
18    4   0.366038964     4   429
18    5   0.430906124     5   430
18    6    0.58128041     6   431
18    7   0.836636999     7   432
18    8   0.369064987     8   433
18    9   0.379906254     9   434
18   10   0.983790767    10   435
18   11   0.514010384    11   436
18   12   0.522375524    12   437
18   13   0.774428551    13   438
18   14   0.368291533    14   439
18   15    0.75101424    15   440
18   16   0.322059441    16   441
18   17   0.119276145    17   442
18   18   0.194016624    18   443
18   19   0.744449809    19   444
18   20   0.111383595    20   445
18   21   0.267825849    21   446
18   22   0.406479934    22   447
18   23   0.803110844    23   448
18   24   0.070320779    24   449
18   25   0.235082917    25   450
19    1   0.941554116     1   451
19    2   0.402766783     2   452
19    3    0.49323547     3   453
19    4   0.143727361     4   454
19    5   0.905338837     5   455
19    6   0.633782663     6   456
19    7   0.824556586     7   457
19    8   0.624209984     8   458
19    9      0.6743865    9   459
19   10   0.968369463    10   460
19   11   0.190588047    11   461
19   12   0.668425569    12   462
19   13   0.384986093    13   463
19   14   0.085945189    14   464
19   15   0.038150001    15   465
19   16   0.991765022    16   466
19   17   0.518763704    17   467
19   18   0.642400481    18   468
19   19    0.16194979    19   469
19   20   0.539692244    20   470
19   21   0.891229703    21   471
19   22   0.584394288    22   472
19   23   0.998963929    23   473
19   24   0.749257792   24   474
19   25   0.497717281   25   475
20    1   0.522259069    1   476
20    2   0.080133889    2   477
20    3   0.485460668    3   478
20    4   0.653449552    4   479
20    5   0.231562815    5   480
20    6   0.473846886    6   481
20    7   0.201716666    7   482
20    8   0.955027197    8   483
20    9   0.620776998    9   484
20   10   0.217515574   10   485
20   11   0.062942977   11   486
20   12   0.387791924   12   487
20   13   0.020257303   13   488
20   14   0.947227464   14   489
20   15   0.492608377   15   490
20   16   0.684632883   16   491
20   17   0.994974381   17   492
20   18   0.777144702   18   493
20   19   0.110770449   19   494
20   20   0.245176626   20   495
20   21   0.592192755   21   496
20   22   0.568678962   22   497
20   23   0.097014532   23   498
20   24   0.051574023   24   499
20   25   0.394042298   25   500
 partial feedback. Controls proportion of feedback in reduced feedback condition

 ck of MCPL learning trials. This should represent the storage allocated.

e this, other changes are required as well. See Program Instructions)



 ck of decision trials. This should represent the storage allocated.




              Low base rate
              Low base rate for UConn experiment 3
              Medium base rate
              High base rate
  Put future base rates here, sort table by base rate
  Put future base rates here, sort table by base rate
  Put future base rates here, sort table by base rate




mance bonus
s the number of
 point X judgment


acy correlation is the
 the judgment and
ng the ideal weights.
r determined by the


 mance bonus, set
 00025 for all
he exponent to 0. If
us, make sure to set
  the intro page to
at only mentions the
at only mentions the
Feedback
condition
Full


Partial




Reduced




Payoff
condition


Equal


Greater
penalty for
false
negatives
Greater
penalty for
false
positives
This text is used to construct the embedded instructions (frmInstEmbed1)
Albany


Feedback text
  After you enter your decision, you will be shown the correct decision, as if an experienced
inspector were by your side teaching you.
After you enter your decision, you will be shown the correct decision, as if an experienced
inspector were by your side teaching you. But if you decide not to search someone, they will
walk out the door and you will not receive any feedback about whether your decision was
right or wrong. This simulates what happens in real life.
After you enter your decision, you will be shown the correct decision, as if an experienced
inspector were by your side teaching you. However, the experienced inspectors have to watch
trainees at other checkpoints, so they won’t be around all the time. When they are not
observing, you won’t be told whether you made the right decision.




Points Story
You don’t want to let smugglers pass, but searching people who are not smuggling is
degrading to them and unpleasant. Too many unnecessary searches may harm our diplomatic
relations with Kenswik, a major trading partner of the U.S. Therefore, you will be penalized
equally for two kinds of incorrect decisions.

 If you let someone through who is smuggling drugs, the drugs will be on the street
contributing to drug addiction and crime. They may be sold to children. Therefore, you are
penalized more severely for this kind of error.
Although your job is to catch drug smugglers, relations between the U.S. and Kenswik are
currently at a very sensitive state. If you search too many nationals from Kenswik, or
mistakenly search a high government official, or a relative of one, you may be fired.
Therefore you are penalized more severely for searches that are not necessary.
Points text
You will receive or lose points
for every decision.
You will receive or lose points
for every decision, even if you
are not told what the correct
decision was.
You will receive or lose points
for every decision, even if you
are not told what the correct
decision was.
                        Payoff amounts
Points lost                                                    Payoff Text (created by concatenating payoff cond
                              True        True       False
      False Negative         positive    Negative   Positive      False Negative

                                                               4. If you decide NO and
                                                               the best decision is YES,
                                                               you are INCORRECT and
            50                 100         100        50       you will lose 50 points.

                                                               4. If you decide NO and
                                                               the best decision is YES,
                                                               you are INCORRECT and
            100                100         100        50       you will lose 100 points.

                                                               4. If you decide NO and
                                                               the best decision is YES,
                                                               you are INCORRECT and
            50                 100         100        100      you will lose 50 points.
created by concatenating payoff condition)


                    True positive                 True Negative           False Positive
                                                2. If you decide NO     3. If you decide YES
            1. If you decide YES and the best   and the best decision   and the best decision
            decision is YES, you are            is NO, you are          is NO, you are
            CORRECT and you will gain 100       CORRECT and you         INCORRECT and you
            points.                             will gain 100 points.   will lose 50 points.
                                                2. If you decide NO     3. If you decide YES
            1. If you decide YES and the best   and the best decision   and the best decision
            decision is YES, you are            is NO, you are          is NO, you are
            CORRECT and you will gain 100       CORRECT and you         INCORRECT and you
            points.                             will gain 100 points.   will lose 50 points.
                                                2. If you decide NO     3. If you decide YES
            1. If you decide YES and the best   and the best decision   and the best decision
            decision is YES, you are            is NO, you are          is NO, you are
            CORRECT and you will gain 100       CORRECT and you         INCORRECT and you
            points.                             will gain 100 points.   will lose 100 points.
Feedback
condition
Full


Partial




Reduced




Payoff
condition


Equal


Greater
penalty for
false
negatives
Greater
penalty for
false
positives
This text is used to construct the embedded instructions (frmInstEmbed1)
Cell names are used by program. Do not change them.
UConn

Feedback text
After you enter your decision, you will be shown the correct decision, as if an experienced
personnel interviewer were by your side teaching you.
After you enter your decision, you will be shown the correct decision, as if an experienced
interviewer were by your side teaching you. But if you decide not to hire someone, he or she
will walk out the door and you will not receive any feedback about whether your decision was
right or wrong. This simulates what happens in real life.
After you enter your decision, you will be shown the correct decision, as if an experienced
interviewer were by your side teaching you. However, the experienced interviewers have to
watch other trainees, so they won’t be around all the time. When they are not observing, you
won’t be told whether you made the right decision.




Points Story


You don’t want to turn away qualified workers, but hiring workers who do not perform
successfully is contrary to our goal of improving homeland security. Therefore, you will be
penalized equally for the two kinds of incorrect decisions.
You do NOT want to turn away qualified workers; good workers are hard to find! And, of
course, hiring workers who do not perform successfully is contrary to our goal of improving
homeland security. Anyone who is hired but then does not perform successfully will be
dismissed during the probationary period. To discourage turning away qualified workers, you
will be penalized differently for the two kinds of incorrect decisions.
You do NOT want to hire unqualified workers, nor do you want to turn away qualified
workers. Hiring workers who do not perform successfully is contrary to our goal of
improving homeland security. To discourage hiring unqualified workers, you will be
penalized differently for the two kinds of incorrect decisions.
Points text
You will receive or lose points
for every decision.
You will receive or lose points
for every decision, even if you
are not told what the correct
decision was.
You will receive or lose points
for every decision, even if you
are not told what the correct
decision was.
                        Payoff amounts
Points lost                                                    Payoff Text (created by concatenating payoff cond
                              True        True       False
      False Negative         positive    Negative   Positive      False Negative

                                                               4. If you decide NO and
                                                               the best decision is YES,
                                                               you are INCORRECT and
            50                 100         100        50       you will lose 50 points.

                                                               4. If you decide NO and
                                                               the best decision is YES,
                                                               you are INCORRECT and
            100                100         100        50       you will lose 100 points.

                                                               4. If you decide NO and
                                                               the best decision is YES,
                                                               you are INCORRECT and
            50                 100         100        100      you will lose 50 points.
created by concatenating payoff condition)


                    True positive                 True Negative           False Positive
                                                2. If you decide NO     3. If you decide YES
            1. If you decide YES and the best   and the best decision   and the best decision
            decision is YES, you are            is NO, you are          is NO, you are
            CORRECT and you will gain 100       CORRECT and you         INCORRECT and you
            points.                             will gain 100 points.   will lose 50 points.
                                                2. If you decide NO     3. If you decide YES
            1. If you decide YES and the best   and the best decision   and the best decision
            decision is YES, you are            is NO, you are          is NO, you are
            CORRECT and you will gain 100       CORRECT and you         INCORRECT and you
            points.                             will gain 100 points.   will lose 50 points.
                                                2. If you decide NO     3. If you decide YES
            1. If you decide YES and the best   and the best decision   and the best decision
            decision is YES, you are            is NO, you are          is NO, you are
            CORRECT and you will gain 100       CORRECT and you         INCORRECT and you
            points.                             will gain 100 points.   will lose 100 points.
Table of values
The row in this table will determine the payoff for each outcome.




                                                    Points lost                                      Points lost
                 Payoff condition              Code False Negative   True positive   True Negative    False Positive
                                  Equal (VE)     VE         50           100              100                50
     Greater penalty for false negatives (VN)    VN        100           100              100                50
      Greater penalty for false positives (VP)   VP         50           100              100               100


Original plan, from proposal (has been revised)
            A. Equal penalty for false positives B. Greater penalty for false         C. Greater penalty for false
                   and false negatives                   negatives                             positives
                              Decision                    Decision                             Decision
             Event     Negative       Positive       Negative    Positive                Negative     Positive
             Positive      50           100             0           100                     50           100
            Negative      100            50            100           50                    100            0
         0 =current subject                              Stats for calculating score and for final decision feedback
        10 =number of cases                                 100      =Pct correct
         5 =number of current case                          100      = Pct positive decisions made
No         =current De             0.502   R2 (500cases)    100      =100*Sample base rate
                                 Threshold                   Sum =         0          1            0
Mean       4.980821              3.569165                   Value=        50         100         100
Std. Dev. 1.58958                  0.802   =base rate       Total =      100     Accumlated over blocks

                                               Accuracy                  False                      True
Case             Ye        Ys         De      Correlation      Ds       Negative   True positive   Negative
         1   6.628849           6     1                             1      0            1             0
         2    5.23407                 1
         3   2.756836                 0
         4   8.835499                 1
         5   6.517632                 1
         6   7.513529                 1
         7   6.041814                 1
         8   6.615223                 1
         9   5.749591                 1
        10   6.589146                 1
                                                                            Don't delete formulas!!
        11   5.693119                 1
        12   8.591425                 1
        13   3.250407                 0
        14   4.842529                 1
        15   4.780322                 1
        16   6.570962                 1
        17   4.984693                 1
        18   4.685442                 1
        19   1.981335                 0
        20   6.443958                 1
        21   3.085308                 0
        22   1.993666                 0       R2 (check)
        23   7.871413                 1        0.6151026
        24   4.674287                 1
        25   7.220755                 1         #DIV/0!
         1   3.602556                 1
         2   2.834636                 0
         3   5.538623                 1
         4   8.225841                 1
         5   5.437145                 1
         6   3.904519                 1
         7   2.880937                 0
         8   4.068754                 1
         9   4.552033                 1
        10   2.671264                 0
        11   4.149025                 1
        12   4.025476                 1
        13    6.72872                 1
        14   1.282098                 0
        15   4.530826                 1
        16   8.009139                 1
17   2.996041   0
18   3.395594   0
19   3.256572   0
20   3.960248   1
21   5.139069   1
22   4.029363   1   R2 (check)
23   5.183331   1    0.3991321
24   3.174886   0
25   5.414523   1    #DIV/0!
 1    3.86352   1
 2   4.245321   1
 3   5.690408   1
 4   7.319642   1
 5   5.640533   1
 6   8.540134   1
 7   6.423183   1
 8   4.893267   1
 9   5.188201   1
10   5.554528   1
11   5.483446   1
12   5.253118   1
13   4.942711   1
14   7.002326   1
15   5.432707   1
16   4.139405   1
17   2.617382   0
18   7.422967   1
19   3.631776   1
20   5.249423   1
21   5.164714   1
22    6.49297   1   R2 (check)
23   3.129449   0    0.5066752
24   5.123716   1
25   4.235893   1    #DIV/0!
 1   1.965861   0
 2   4.350805   1
 3    7.60354   1
 4   1.949092   0
 5   4.591857   1
 6   3.004485   0
 7    5.23407   1
 8   5.453914   1
 9   4.767872   1
10   7.910684   1
11   3.373092   0
12   6.692903   1
13   5.121988   1
14     8.3812   1
15   4.622684   1
16    5.21946   1
17   3.215022   0
18   5.604835   1
19   5.342145   1
20   3.320074   0
21   6.543277   1
22   7.419393   1
23   3.287951   0
24   5.869997   1
25   6.451851   1   #DIV/0!
 1   4.025908   1
 2   5.469268   1
 3   5.673639   1
 4   3.431843   0
 5   3.533753   0
 6   1.539487   0
 7   4.909605   1
 8   3.920424   1
 9    5.25614   1
10   4.619661   1
11   4.457585   1
12   3.296276   0
13   2.316283   0
14   5.931891   1
15   4.243162   1
16   2.201611   0
17   5.042893   1
18   5.364216   1
19   3.600829   1
20   3.242946   0
21   6.947149   1
22   5.946933   1
23   3.653847   1
24   4.232007   1
25   5.949524   1   #DIV/0!
 1   4.167641   1
 2   5.837011   1
 3   4.476633   1
 4   3.853348   1
 5    2.75782   0
 6   5.761922   1
 7   4.134535   1
 8   5.267176   1
 9   6.848262   1
10   4.255805   1
11   8.231575   1
12   1.053929   0
13   3.218164   0
14   2.514609   0
15   3.722219   1
16   4.755109   1
17   6.925078   1
18   6.841113   1
19   3.928437   1
20   5.203986   1
21   2.963054   0
22   4.814724   1
23   4.447965   1
24   3.524133   0
25   6.527803   1   #DIV/0!
 1   6.191439   1
 2   5.333268   1
 3    6.24748   1
 4   4.175102   1
 5   4.304504   1
 6   5.543061   1
 7   6.823049   1
 8   5.181052   1
 9   5.898353   1
10   4.207345   1
11   2.962191   0
12   3.306448   0
13   4.324296   1
14   6.734765   1
15   5.741698   1
16     5.2755   1
17   2.544141   0
18    9.10781   1
19   6.710535   1
20   4.853132   1
21   2.909605   0
22   3.400464   0
23   3.723082   1
24    6.10402   1
25   5.498368   1   #DIV/0!
 1   8.555176   1
 2   5.090609   1
 3   4.132256   1
 4   7.553545   1
 5   5.229512   1
 6   6.178677   1
 7   5.867958   1
 8   2.388661   0
 9   6.216221   1
10   6.102292   1
11   1.419824   0
12    4.17954   1
13   4.048843   1
14   3.561557   0
15   5.042461   1
16   5.956121   1
17   6.643459   1
18   7.225625   1
19   5.295844   1
20   3.716485   1
21   7.282649   1
22   5.415386   1
23   3.977328   1
24   4.946717   1
25   5.192087   1   #DIV/0!
 1   5.135183   1
 2   5.042461   1
 3    3.30472   0
 4   6.390077   1
 5   6.210799   1
 6   5.188633   1
 7   3.576599   1
 8   7.707609   1
 9   6.633719   1
10   5.314772   1
11   5.117982   1
12   7.864935   1
13   6.180836   1
14   7.871844   1
15    5.23407   1
16   5.418529   1
17   4.370597   1
18   2.954178   0
19   2.581253   0
20   5.241099   1
21   5.445902   1
22   5.213294   1
23   5.749159   1
24   6.532122   1
25   3.807359   1   #DIV/0!
 1   3.704586   1
 2   5.498919   1
 3   5.645403   1
 4   2.501294   0
 5   5.453362   1
 6    1.77123   0
 7   6.652648   1
 8   4.467756   1
 9   3.759763   1
10   6.562205   1
11   2.332741   0
12   4.846967   1
13   5.245105   1
14   6.432491   1
15   3.199236   0
16   4.029051   1
17   3.278211   0
18   4.404999   1
19   5.320074   1
20   5.207009   1
21   6.961639   1
22   4.173807   1
23   5.460511   1
24   4.473058   1
25   3.369949   0   #DIV/0!
 1   3.117118   0
 2   4.543277   1
 3   4.869781   1
 4   6.542845   1
 5   5.897802   1
 6   5.505949   1
 7   3.505949   0
 8   5.154111   1
 9   5.929732   1
10   3.110953   0
11   4.953746   1
12   5.793301   1
13   2.584276   0
14   3.872276   1
15   6.399385   1
16   6.751534   1
17   6.412699   1
18   5.383264   1
19   5.631776   1
20   6.051122   1
21   9.272909   1
22   7.958832   1
23   5.272046   1
24   4.295196   1
25   0.087251   0   #DIV/0!
 1   6.108458   1
 2   5.537759   1
 3   5.715189   1
 4   3.658285   1
 5   5.478576   1
 6   5.439304   1
 7   3.093632   0
 8   6.942711   1
 9   4.569666   1
10   6.411716   1
11   7.286968   1
12   3.311749   0
13   3.479008   0
14   3.373955   0
15    6.67527   1
16   5.907542   1
17   5.264897   1
18    4.75295   1
19   4.838522   1
20   5.374939   1
21   4.580821   1
22   5.775548   1
23   5.801745   1
24   3.871844   1
25   -0.11798   0   #DIV/0!
 1   6.206049   1
 2   5.832141   1
 3   2.272262   0
 4   6.083244   1
 5   5.918577   1
 6   3.148377   0
 7    4.70437   1
 8   3.583196   1
 9    6.84296   1
10    6.50746   1
11   4.905718   1
12   5.591641   1
13   4.779027   1
14   6.632856   1
15   6.333604   1
16   3.510267   0
17   6.929204   1
18   3.038455   0
19    7.21459   1
20   3.478144   0
21   6.604619   1
22   7.520127   1
23   3.503789   0
24   4.926374   1
25   5.388997   1   #DIV/0!
 1   7.209288   1
 2   6.174239   1
 3   4.079358   1
 4   2.283729   0
 5    6.96922   1
 6   4.691056   1
 7   3.060094   0
 8   3.837443   1
 9   4.984262   1
10   5.533321   1
11   3.229631   0
12   3.580486   1
13   4.841665   1
14   5.000167   1
15   7.015089   1
16   4.181268   1
17   4.326455   1
18   6.299634   1
19   1.727089   0
20   3.762354   1
21   5.142332   1
22   4.779459   1
23   4.302657   1
24   4.233734   1
25   7.291838   1   #DIV/0!
 1   5.846319   1
 2   4.878346   1
 3   3.710751   1
 4   7.197821   1
 5   6.079358   1
 6   8.440816   1
 7   8.250623   1
 8   4.790374   1
 9   6.365847   1
10   5.487884   1
11   5.730663   1
12   5.616734   1
13   2.897274   0
14   6.763985   1
15   5.354907   1
16   4.367574   1
17   7.163851   1
18   2.635879   0
19   4.280466   1
20   8.163635   1
21   4.587419   1
22   5.068538   1
23   4.675702   1
24    4.13108   1
25   3.305152   0   #DIV/0!
 1   5.339554   1
 2   6.374603   1
 3   2.826623   0
 4    5.45521   1
 5    6.34464   1
 6   5.343992   1
 7   2.375899   0
 8   4.280154   1
 9   5.796324   1
10   4.425774   1
11   2.813429   0
12   4.872492   1
13   3.844592   1
14   7.196093   1
15   3.286104   0
16   5.300162   1
17   5.928317   1
18   4.441247   1
19    4.17467   1
20   6.290326   1
21   3.672343   1
22   2.831061   0
23   5.746017   1
24   3.084012   0
25   1.929732   0   #DIV/0!
 1   4.085092   1
 2   6.105315   1
 3   3.653415   1
 4   4.525956   1
 5   7.792437   1
 6   4.885375   1
 7   7.651136   1
 8   5.324512   1
 9   5.751007   1
10   2.248344   0
11   4.668553   1
12   6.555608   1
13   3.307743   0
14   1.456073   0
15   4.695062   1
16   5.483878   1
17   4.856587   1
18   4.124363   1
19   4.716269   1
20   6.047547   1
21   6.499135   1
22   3.410636   0
23   5.924862   1
24   6.991291   1
25    3.06897   0   #DIV/0!
 1   4.263385   1
 2   6.329166   1
 3   2.577247   0
 4   7.585356   1
 5   3.761922   1
 6   5.523149   1
 7   5.445902   1
 8   5.388014   1
 9   5.989347   1
10   6.026772   1
11    5.73726   1
12   3.610137   1
13   4.402408   1
14   3.709888   1
15    7.14178   1
16   6.676134   1
17   9.023965   1
18    6.25722   1
19   3.818514   1
20   2.160924   0
21   2.859729   0
22    4.77718   1
23   1.903655   0
24   5.067555   1
25   3.918577   1   #DIV/0!
 1   6.189712   1
 2   6.895427   1
 3   4.289343   1
 4   3.298555   0
 5     7.2755   1
 6    7.98263   1
 7   4.899865   1
 8    4.59001   1
 9   4.256788   1
10   2.177261   0
11   3.411932   0
12    6.33977   1
13   4.081949   1
14   4.902144   1
15   7.259715   1
16     4.8064   1
17   6.388781   1
18   5.120693   1
19   7.163851   1
20   2.018879   0
21    6.68976   1
22    4.63643   1
23   4.669848   1
24   4.238172   1
25   4.682299   1   #DIV/0!
 1   3.366495   0
 2   3.956553   1
 3   8.482798   1
 4   4.571945   1
 5    4.39581   1
 6   2.170664   0
 7   7.302009   1
 8   5.870549   1
 9   5.499351   1
10   3.625179   1
11   3.667473   1
12   4.481503   1
13   4.845551   1
14   2.736181   0
15   6.324728   1
16   4.236996   1
17   6.519359   1
18   4.453147   1
19    4.64617   1
20   3.585356   1
21   6.565348   1
22   7.778691   1
23   4.960344   1
24   5.049059   1
25   3.362488   0   #DIV/0!
r final decision feedback
               1          = Total decisions made


                    0
                   50       4.044       3.858      4.044   #DIV/0!   #DIV/0!   0.000   0.000   0.000
ed over blocks              2.269       2.239      2.271   #DIV/0!   #DIV/0!   0.000   0.000   0.000

                  False
                 Positive   Cue 1       Cue 2      Cue 3   Cue 4     Cue 5     Cue 6   Cue 7   Cue 8
                    0         7           7          2                           0       0       0
                              2           2          7                           0       0       0
                              5           1          7                           0       0       0
                              3           7          4                           0       0       0
                              6           6          3                           0       0       0
                              1           3          7                           0       0       0
                              7           5          2                           0       0       0
                              1           7          2                           0       0       0
                              1           7          3                           0       0       0
                              6           4          6                           0       0       0
                              7           1          7
                              7           3          6
                              3           2          2
                              6           3          3
                              3           1          6
                              6           7          7
                              2           4          2
                              3           3          1
                              7           1          1
                              7           2          6
                              2           1          5
                              6           2          2
                              2           7          7
                              5           6          3
                              7           6          6
                              6           2          7
                              1           1          2
                              2           6          2
                              5           7          7
                              7           2          2
                              1           5          3
                              2           2          3
                              1           2          6
                              6           6          1
                              6           1          2
                              3           7          1
                              3           2          6
                              6           1          5
                              5           2          3
                              6           5          4
                              7           6          5
2   7   2
2   1   7
7   1   2
1   1   2
1   7   6
3   5   7
1   5   1
1   2   6
7   6   3
6   2   1
3   3   3
1   6   7
6   6   6
4   7   3
6   7   6
6   6   2
4   3   6
3   3   2
2   6   1
1   7   1
5   1   2
2   3   7
1   6   5
6   1   6
6   2   1
3   1   6
5   5   6
2   3   2
6   5   6
1   7   3
6   3   4
2   1   5
7   3   2
6   6   7
2   1   6
1   2   7
1   7   3
4   3   1
6   2   1
1   2   7
2   2   7
7   1   4
3   6   4
6   6   7
5   3   1
7   5   2
5   1   4
7   7   7
7   1   7
3   7   1
7   1   6
6   2   6
6   7   1
1   3   7
3   6   2
7   6   6
3   1   2
7   7   6
7   6   3
5   4   2
6   6   3
2   6   6
4   1   2
7   1   4
1   3   1
6   5   1
7   2   3
5   2   5
5   2   2
7   5   1
7   2   2
2   6   2
7   6   1
6   1   1
3   1   3
7   3   5
7   3   7
7   3   2
1   1   2
7   3   6
7   1   7
3   2   3
7   2   7
2   6   6
1   1   7
2   7   1
1   1   7
3   1   6
1   2   1
6   5   5
7   1   3
2   2   7
2   6   5
6   7   2
7   7   6
2   2   2
4   3   1
1   1   2
7   3   2
6   5   1
1   6   5
7   7   6
4   1   2
5   6   3
1   3   1
1   6   1
6   1   2
2   1   1
7   3   6
6   3   7
6   6   6
2   6   6
6   2   5
5   2   1
1   6   1
6   6   6
1   5   6
2   7   2
1   2   7
1   1   3
6   1   3
6   4   2
6   6   6
1   6   1
6   3   7
4   1   3
3   7   7
7   6   2
2   3   5
7   1   3
1   2   5
7   2   5
7   7   1
7   7   3
6   5   7
2   5   2
2   6   3
7   7   7
6   7   6
1   4   6
3   1   7
1   7   2
2   2   7
1   6   4
1   4   2
2   5   1
6   2   6
2   5   1
7   5   1
5   7   4
5   3   7
3   7   6
6   2   6
2   3   5
4   5   3
3   6   7
7   3   4
7   2   3
3   6   3
6   2   5
7   2   6
2   1   3
6   6   2
5   6   7
3   1   6
2   3   2
6   7   7
7   7   1
3   6   5
3   5   1
1   2   6
6   7   1
7   6   6
2   2   7
1   7   3
6   6   2
5   1   5
2   1   2
7   2   6
7   2   7
7   3   4
7   3   5
7   7   6
1   7   3
4   2   4
2   2   7
2   6   5
1   1   7
3   6   6
6   1   1
6   6   7
1   3   7
2   1   7
5   5   6
3   1   1
5   3   2
2   5   2
7   1   7
1   2   1
1   1   6
2   2   3
6   6   4
2   5   7
6   6   7
5   7   6
5   3   2
5   1   7
2   3   6
7   2   5
2   1   3
3   3   3
6   6   6
7   1   7
6   7   7
2   7   1
7   2   2
1   5   7
2   3   6
1   2   1
6   5   1
2   5   5
2   2   5
1   7   1
2   6   2
5   6   7
7   1   2
1   5   3
7   4   1
6   2   5
2   7   7
6   7   3
7   3   1
6   2   3
1   2   1
7   3   6
5   1   7
2   3   7
6   1   1
5   6   1
2   6   2
3   5   2
7   7   1
2   5   7
6   5   3
3   7   7
1   1   6
5   1   6
3   1   7
7   1   7
3   7   7
6   7   1
7   2   2
5   6   1
6   1   2
7   1   2
7   7   5
6   1   5
7   3   3
1   1   1
4   5   2
6   3   6
1   2   1
1   7   7
7   6   6
1   6   1
1   6   1
7   2   2
6   7   1
5   6   5
1   1   5
1   2   6
3   1   4
2   7   3
2   7   1
4   6   4
1   2   1
2   3   6
3   7   6
3   1   6
6   6   1
6   2   7
2   2   2
4   6   1
2   3   6
6   6   6
6   6   1
7   1   3
2   2   1
7   3   6
3   7   3
2   2   7
3   4   2
7   1   3
5   2   7
6   2   2
1   4   7
2   2   6
6   2   1
2   6   7
2   6   2
5   7   1
5   2   6
2   2   2
3   3   7
1   1   4
1   1   6
6   2   6
1   6   7
6   7   4
2   3   5
6   1   2
1   2   7
1   7   7
2   6   2
6   7   6
7   6   3
4   6   4
6   1   7
1   6   1
2   2   7
4   6   2
1   1   5
2   4   6
7   7   3
6   2   4
4   5   7
1   6   2
7   6   7
3   7   6
6   3   1
1   6   1
1   2   6
2   1   1
6   1   1
6   1   7
1   6   7
2   1   6
7   1   6
7   5   1
7   2   3
3   4   3
6   1   7
5   6   6
6   6   2
3   1   2
7   6   1
3   1   1
7   3   7
2   3   5
2   7   7
4   6   6
6   2   7
1   6   1
1   7   3
7   1   5
2   3   1
2   6   7
1   2   2
1   1   2
3   1   6
1   7   7
6   1   2
2   6   6
2   6   6
1   5   1
6   7   5
6   3   6
7   2   1
5   2   4
7   5   3
6   6   2
2   2   6
2   2   1
1   7   2
7   5   1
1   6   6
2   2   6
3   6   1
5   6   2
3   3   7
2   2   3
1   7   1
7   3   6
1   1   6
7   1   6
3   7   2
1   1   5
4   7   7
6   2   6
7   2   7
3   6   3
6   5   7
5   2   4
2   6   6
2   6   2
2   1   6
3   3   7
5   2   3
7   5   5
7   3   5
7   5   6
5   6   2
5   1   2
5   1   7
2   1   6
1   7   1
6   1   1
3   7   5
6   7   1
6   5   1
6   6   7
6   5   6
2   1   2
2   7   7
7   7   5
4   7   1
6   3   5
1   3   5
2   5   2
3   1   6
1   5   6
2   6   2
6   2   3
5   5   1
3   2   2
2   7   1
1   2   3
7   5   5
3   1   2
5   5   7
7   2   1
3   6   6
6   6   2
1   3   6
5   2   1
7   6   1
2   6   7
6   1   6
2   3   6
1   2   6
2   6   7
3   4   6
6   2   5
1   3   1
3   2   7
7   1   2
7   6   2
2   2   1
1   7   5
2   2   1
3   7   6
2   5   6
5   1   2
6   2   6
7   5   1
7   6   7
2   7   2
7   6   1
1   2   6
                                0.707104 Re, the correlation between Y calculated from weights and the Ye used for d
                                     3.95
                                     1.33 Standard deviation

0.000   0.000
0.000   0.000

                 Feedback   Y calculated   Std Dev
Cue 9   Cue 10     Given    from weights     Ys    Block
  0       0                         5.50                      1
  0       0                         3.50                      1
  0       0                         3.60                      1
  0       0                         5.30                      1
  0       0                         5.10                      1
  0       0                         3.80                      1
  0       0                         4.50                      1
  0       0                         4.30                      1
  0       0                         4.60                      1
  0       0                         5.00                      1
                                    4.00                      1
                                    4.70                      1
                                    2.20                      1
                                    3.60                      1
                                    2.90                      1
                                    6.80                      1
                                    3.00                      1
                                    2.40                      1
                                    2.20                      1
                                    4.20                      1
                                    2.40                      1
                                    2.80                      1
                                    6.00                      1
                                    4.90                      1
                                    6.20           0          1
                                    4.30                      2
                                    1.30                      2
                                    4.00                      2
                                    6.60                      2
                                    3.00                      2
                                    3.60                      2
                                    2.30                      2
                                    3.00                      2
                                    4.50                      2
                                    2.30                      2
                                    4.40                      2
                                    3.40                      2
                                    3.20                      2
                                    2.90                      2
                                    4.90                      2
                                    5.90                      2
4.50             2
3.00             2
2.50             2
1.30             2
5.50             2
5.20             2
3.00             2
3.00             2
5.30   #DIV/0!   2
2.50             3
3.00             3
5.30             3
6.00             3
5.20             3
6.50             3
4.80             3
4.10             3
2.70             3
3.70             3
4.00             3
2.10             3
4.00             3
4.70             3
3.50             3
2.50             3
2.90             3
5.30             3
2.50             3
5.50             3
4.60             3
3.90             3
2.40             3
3.50             3
6.30   #DIV/0!   3
2.70             4
3.30             4
4.60             4
2.60             4
2.50             4
3.30             4
3.50             4
3.10             4
4.80             4
6.30             4
2.80             4
4.50             4
2.70             4
7.00             4
4.00             4
4.40             4
3.70             4
4.00             4
5.00             4
3.80             4
4.20             4
6.20             4
1.70             4
6.70             4
5.30   #DIV/0!   4
3.60             5
5.10             5
5.20             5
1.90             5
3.10             5
2.00             5
4.00             5
3.30             5
3.50             5
2.60             5
4.20             5
3.00             5
4.00             5
4.70             5
2.00             5
2.00             5
4.40             5
5.00             5
3.50             5
1.30             5
4.70             5
4.00             5
2.50             5
4.50             5
5.20   #DIV/0!   5
2.80             6
4.20             6
2.80             6
2.90             6
1.50             6
5.20             6
2.80             6
3.50             6
4.90             6
5.30             6
6.70             6
2.00             6
2.60             6
1.30             6
3.50             6
4.00             6
4.70             6
6.70             6
1.90             6
4.90             6
2.00             6
3.50             6
2.30             6
1.20             6
4.70   #DIV/0!   6
4.80             7
6.00             7
5.20             7
3.70             7
2.30             7
3.50             7
6.00             7
4.50             7
4.50             7
3.30             7
1.60             7
2.60             7
3.80             7
6.00             7
3.50             7
4.80             7
2.20             7
6.20             7
5.00             7
3.40             7
2.80             7
2.70             7
3.90             7
5.20             7
5.80   #DIV/0!   7
5.80             8
3.50             8
4.30             8
7.00             8
6.50             8
4.00             8
3.20             8
4.30             8
3.50             8
4.40             8
2.80             8
3.20             8
4.00             8
3.20             8
4.20             8
5.70             8
4.60             8
5.90             8
4.00             8
3.40             8
4.20             8
5.70             8
4.10              8
3.30              8
4.50   #DIV/0!    8
3.70              9
4.20              9
1.80              9
4.80              9
6.10              9
2.90              9
2.50              9
6.80              9
5.20              9
5.10              9
3.40              9
3.00              9
5.00              9
6.20              9
3.50              9
4.60              9
4.80              9
3.00              9
1.50              9
4.20              9
4.50              9
4.10              9
4.40              9
6.70              9
4.60   #DIV/0!    9
3.00             10
3.50             10
4.90             10
2.80             10
5.40             10
2.00             10
6.30             10
3.80             10
3.00             10
5.30             10
1.40             10
3.10             10
3.50             10
4.00             10
1.50             10
2.50             10
2.30             10
5.40             10
5.00             10
6.30             10
6.30             10
3.10             10
3.60             10
3.70             10
3.90   #DIV/0!   10
1.80             11
3.00             11
6.00             11
4.00             11
6.80             11
4.20             11
3.00             11
4.80             11
3.70             11
1.50             11
4.00             11
4.40             11
2.90             11
4.00             11
4.00             11
6.10             11
2.50             11
3.60             11
3.70             11
3.70             11
6.00             11
5.60             11
3.20             11
3.10             11
1.50   #DIV/0!   11
4.70             12
3.60             12
4.00             12
2.00             12
4.30             12
4.00             12
3.70             12
5.20             12
5.00             12
4.60             12
6.20             12
2.50             12
3.30             12
3.20             12
4.00             12
6.20             12
5.00             12
3.00             12
4.30             12
2.30             12
2.50             12
6.40             12
3.20             12
3.80             12
1.00   #DIV/0!   12
3.90             13
4.50             13
1.50             13
5.80             13
6.20             13
3.50             13
3.50             13
3.00             13
5.00             13
5.50             13
2.20             13
3.00             13
2.30             13
4.80             13
4.20             13
5.00             13
1.50             13
3.70             13
5.90             13
2.90             13
4.50             13
4.30             13
2.00             13
4.10             13
3.70   #DIV/0!   13
6.00             14
4.50             14
2.80             14
1.70             14
4.70             14
5.00             14
3.50             14
3.20             14
2.80             14
4.10             14
2.80             14
4.30             14
3.20             14
2.50             14
5.50             14
4.00             14
4.80             14
3.80             14
2.00             14
4.20             14
1.90             14
2.50             14
4.00             14
5.30             14
5.90   #DIV/0!   14
3.40             15
2.30             15
3.30             15
5.80             15
4.00             15
6.50             15
5.30             15
5.00             15
3.80             15
3.50             15
3.50             15
4.40             15
2.20             15
4.20             15
5.80             15
3.40             15
5.40             15
3.80             15
6.50             15
5.90             15
3.00             15
3.50             15
3.00             15
1.20             15
2.00   #DIV/0!   15
3.80             16
5.30             16
2.70             16
3.70             16
4.20             16
3.30             16
3.50             16
3.80             16
5.80             16
4.80             16
1.70             16
4.70             16
1.40             16
5.00             16
3.40             16
6.00             16
5.60             16
4.30             16
3.50             16
4.60             16
3.40             16
2.20             16
5.50             16
1.80             16
1.30   #DIV/0!   16
2.90             17
5.80             17
2.30             17
5.20             17
5.20             17
3.00             17
6.20             17
4.50             17
2.70             17
3.20             17
4.80             17
4.80             17
3.20             17
1.70             17
4.30             17
4.20             17
5.00             17
3.20             17
3.90             17
4.60             17
4.20             17
2.30             17
4.00             17
4.70             17
2.50   #DIV/0!   17
3.70             18
4.70             18
2.20             18
6.40             18
4.00             18
4.50             18
4.50             18
5.80             18
3.20             18
5.20             18
4.00             18
2.70             18
4.20             18
2.90             18
5.40             18
4.40             18
5.70             18
4.60             18
2.10             18
3.60             18
2.70             18
4.00             18
2.00             18
5.60             18
5.00   #DIV/0!   18
4.00             19
6.30             19
5.50             19
1.50             19
6.00             19
6.40             19
4.60             19
4.20             19
3.20             19
3.50             19
2.90             19
4.50             19
4.00             19
3.10             19
3.80             19
2.20             19
4.20             19
2.10             19
5.40             19
1.70             19
5.60             19
2.70             19
5.40             19
4.80             19
3.50   #DIV/0!   19
2.30             20
4.70             20
5.50             20
3.50             20
3.70             20
3.00             20
5.50             20
4.40             20
3.70             20
2.00             20
3.70             20
2.50             20
5.00             20
1.70             20
5.20             20
1.70             20
5.90             20
4.70             20
2.10             20
4.00             20
4.20             20
6.50             20
4.50             20
4.70             20
3.00   #DIV/0!   20
m weights and the Ye used for decision cutoff
Range of choices forcombo boxes on SubjectReport
  0-10       0-100
       10        100
        9          95
        8          90
        7          85
        6          80
        5          75
        4          70
        3          65
        2          60
        1          55
        0          50
                   45
                   40
                   35
                   30
                   25
                   20
                   15
                   10
                    5
                    0
         0 =current subject
        10 =number of cases
         1 =number of current case
                       #VALUE! =Rs          Task Development Spreadsheet
                         #DIV/0! =ra
Mean       4.980821 #DIV/0!          4.25    3.428571 3.678571 #DIV/0!     #DIV/0!   #DIV/0!
Std. Dev. 1.58958 #DIV/0!         2.369825 2.274526 2.204761 #DIV/0!       #DIV/0!   #DIV/0!
Case           Ye         Ys        Cue 1      Cue 2    Cue 3     Cue 4     Cue 5     Cue 6
         1     5                          1          1        7
         2     5                          7          1        2
         3     6                          2          2        6
         4     4                          2          3        1
         5     6                          6          3        6
         6     6                          6          5        4
         7     4                          7          2        2
         8     3                          2          1        1
         9     7                          6          3        7
        10     7                          7          2        6
        11     9                          3          6        6
        12     7                          1          7        5
        13     3                          6          1        5
        14     5                          1          7        1
        15     4                          7          1        2
        16     5                          5          1        6
        17     6                          5          7        2
        18     3                          4          2        1
        19     5                          1          7        2
        20     4                          2          2        6
        21     4                          2          1        2
        22     7                          1          6        6
        23     6                          2          3        5
        24     5                          7          2        1
        25     7                          7          6        1

Example Cases
             Ye          Ys      Cue 1      Cue 2     Cue 3
              5                    6          5         2
              3                    7          2         2
              8                    6          7         6
#DIV/0!   #DIV/0!   #DIV/0!   #DIV/0!
#DIV/0!   #DIV/0!   #DIV/0!   #DIV/0!
 Cue 7     Cue 8     Cue 9    Cue 10
                                        Comparison of your weights with ideal weights
The program has analyzed your
judgments from the last set to          after completing set   1
determine how you tended to weigh
the three items of information. The                               Your weight   Ideal weight
results are in the chart.
                                                  60
The ideal weights you are trying to
use are in purple. The weights you
                                                  50
generally used over the last set of
cases are in blue. We don't expect a
perfect match, but we hope you can                40
get close.




                                         Weight
                                                  30
If your weights match the ideal
weights, continue practicing what
you are doing. If your weights don't              20
match up well, study the differences
and try to put more or less weight on             10
the right information.
                                                  0
Press Continue when you are ready
to go on.                                              Clothing       Emotionality
                                                                        Information
ights with ideal weights



           Ideal weight




                                    Note to testers. If you
                                    have judged fewer than
                                    25 passengers, you
                                    won't get the bars
                                    showing your actual
                                    weights.




  Emotionality            Bulging
   Information
                                        Comparison of your weights with ideal weights
The program has analyzed your
judgments from the last set to          after completing set   1
determine how you tended to weigh
the three items of information. The                                       Your weight   Ideal weight
results are in the chart.
                                                  60
The ideal weights you are trying to
use are in purple. The weights you
                                                  50
generally used over the last set of
cases are in blue. We don't expect a
perfect match, but we hope you can                40
get close.




                                         Weight
                                                  30
If your weights match the ideal
weights, continue practicing what
you are doing. If your weights don't              20
match up well, study the differences
and try to put more or less weight on             10
the right information.
                                                  0
Press Continue when you are ready
to go on.                                              Emotional maturity Attention to detail
                                                                                Information
ights with ideal weights



            Ideal weight




                                             Note to testers. If you
                                             have judged fewer than
                                             25 passengers, you
                                             won't get the bars
                                             showing your actual
                                             weights.




Attention to detail    Interpersonal skill
    Information
              #N/A     Accuracy
                       Relative weight
Cue      Beta Weight     Your weight     Ideal weight
Cue 1        #VALUE!      #VALUE!            20.0
Cue 2        #VALUE!      #VALUE!            50.0
Cue 3        #VALUE!      #VALUE!            30.0
Cue 4
Cue 5
Cue 6
Cue 7
Cue 8
Cue 9
Cue 10
SumAbs      #VALUE!       #VALUE!                 100
This is Elise's demographics sheet
Gender
Male
Female

Age
18 - 19
20 - 24
25 - 29
30 - 34
35 - 44
45 - 54
55 - 64
65 - 69
70 - 74
75 or older

Education
Less than high school
High school graduate
Some college
2-year college degree
4-year college degree
Some graduate school
Graduate degree

Favorite Baseball Team
Boston Red Sox
Boston Red Sox
Boston Red Sox
Boston Red Sox
Boston Red Sox
Boston Red Sox
Boston Red Sox

Mathematics
I have never had any math classes
I had the required high school math classes
I took more math than required in high school
I took some math in college
I majored in a quantitative course in college

Statistics
I have never taken a statistics course
I have taken a statistics course
I have taken at least 3 statistics courses

English Language
English is my first language
English is not my first language, but I'm fluent
English is my second language, and I'm still learning
Please Select from List Below
Please Select from List Below
Please Select from List Below
Please Select from List Below
Please Select from List Below
Please Select from List Below
Please Select from List Below
              Weights Sum to 100
    Cue1             50  33
    Cue2             50  33
    Cue3             50  33
                    150

      Accuracy       50
   Cutoff Value       5
  Used cutoff? Yes
Percent Correct      50
     Base Rate       50
     Last cue
     n          n-1        n-2        n-3        n-4        n-5        n-6        n-7
b     #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!
se    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!
r2    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!
F     #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!
ss    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!    #VALUE!

                    Space is reserved here for 10 cues. To change the LINEST formula, highlight all the cells,
                    Insert/formula/LINEST, and after filling out the form, press CTRL-SHFT-ENTER to enter the array
                    formula. You can also change the formula in the formula bar. X columns cannot contain blank da
            n-8        n-9        n-10       Constant
             #VALUE!    #VALUE!    #VALUE!   #VALUE!
             #VALUE!    #VALUE!    #VALUE!   #VALUE!
             #VALUE!    #VALUE!    #VALUE!   #VALUE!
             #VALUE!    #VALUE!    #VALUE!   #VALUE!
             #VALUE!    #VALUE!    #VALUE!   #VALUE!

ormula, highlight all the cells,
           ENTER to enter the array
 X columns cannot contain blank data.
The proportion of positive decisions, determined by the average of
people who have completed partial feedback.                          0.0000

                                                                         0
= Proportion of feedback cases needed, based on mean number
of positive decisions made by subjects in partial feedback
= Reduced Feedback Control (O, no feedback, 1, feedback
             Worksheet   Form                             Action          Result
             Intro                                Run                     Runs Main, switches to Blank sheet, shows frmWelc
             Blank       frmWelcome               OK                      frmMCPLinstructions
             Blank       frmMCPLinstructions      OK                      set CaseNum = 0, frmPresentCases
             Blank       frmPresentCases          OK                      Store Data, present next case, switch to frmFeedbac
             Blank       frmPresentCases          Click case image        Show frmCueHelp -- reminder of cue definitions


Start program from
INTRO worksheet                             CondR2
sub Main                                     Low?
Module1MCPL                                  Med?
                                             High?


Initialize
Block = 0
                                    Load training block of
                                    cases into
                                    TaskDataMCPL with
                                    appropriate task R2 for
                                    Block
                                    Block = Block+1

Welcome and general
instructions
frmWelcome
                                     Present training block
                                     of cases with
                                     appropriate task R2
Demographics form
                                     frmPresentCases
frmDemographics
                                                                     NO

                                     Present cognitive
                                     feedback. All
MCPL instructions
                                     subjects must do 3
frmMCPLinstructions
                                     blocks of cases.




                                            Have all
                                           blocks of
                                          cases been
                                          completed?



                                                    Yes.

                                    Go to decision task.
 to Blank sheet, shows frmWelcome

mPresentCases
 ext case, switch to frmFeedbackBlock1
reminder of cue definitions
                 User form size to fill screen        576        768
Text box size for instructions and text pages         450        650
        Background color of user forms         White
        Background color of buttons            Black, white text
        Size of buttons                                30         90
        Display of cues for each case                 300        400

        Screen size calculations for forms Screen resolution     Form Sizs
                                           DPI       Width       Height     Width     Height
                                      XGA         96        1024        778    767.65     582.4
                                                  96        1400      1050 1049.521 786.0154
                                     ESB19       120        1400      1050 839.6172 628.8123
                      Naming Condtions
                      RL,RM,RH R2 (Low, Medium, High)
                      BL,BM,BH Base Rate (Low, Medium, High)
                      VE,VN,VP Value structure (Equal, Greater penalty for false negatives, greater penalty for false po
                      FF,FP,FR  Feedback (Full, conditional, partial) (formerly Full, partial,reduced)

                       Condition lookup tables
                       R2/Certainty
                                 0.5 RL
                                 0.7 RM
                                 0.9 RH
                       Base Rate
                                 0.1 BL
                                 0.5 BM
                                 0.8 BH
                       Value Structure
                               Equal VE
Greater penalty for false negatives VN
Greater penalty for false positives VP
                         Feedback
                       Conditional FP
                       Full          FF
                       Partial       FR
es, greater penalty for false positives

								
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