# 190 | ResearchBox


ResearchBox # 190 - 'Generation and choice rely on distinct value forms'


Bingo Table
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Pilot


  Pilot.pdf



  Pilot.qsf


  


  pilot_data.csv



  pilot_code.R



  pilot_output.rdata


Simulations


  sims.m



  sims.R


Studies 1-2


  study1-2_code.R


Studies 4-6


  study4-6_code.R



  study4-6_aggregated_code.R



  study4-6_aggregated_output.rdata


Studies 4-7, 9


  utilities.js



  savedata.php



  end.php


Study 1


  Study1.pdf



  Study1.qsf


  


  study1_data.csv



  study1_output.rdata


Study 2


  Study2.pdf



  Study2.qsf


  


  study2_data.csv



  study2_output.rdata


Study 3


  Study3.pdf



  Study3.qsf


  


  study3_data.csv



  study3_code.R



  study3_output.rdata


Study 4


  Study4-index.html


  


  study4_demo.csv


  


  study4_words.csv


  


  study4_s1.csv


  


  study4_s2.csv



  study4_output.rdata


Study 5


  Study 5 - AsPredicted #14220.pdf



  Study5-index.html


  


  study5_demo.csv


  


  study5_words.csv


  


  study5_s1.csv


  


  study5_s2.csv



  study5_output.rdata


Study 6


  Study6-index.html


  


  study6_demo.csv


  


  study6_words.csv


  


  study6_s1.csv


  


  study6_s2.csv



  study6_output.rdata


Study 7


  Study 7 - AsPredicted #45132.pdf



  Study7-index.html


  


  study7_demo.csv


  


  study7_words.csv


  


  study7_s1.csv.zip


  


  study7_s2.csv



  study7_code.R


(23 Mb)


  study7_output.rdata


Study 8


  Study8.pdf



  Study8.qsf


  


  study8_data.csv



  study8_code.R



  study8_output.RData


Study 9


  Study9-index.html


  


  study9_demo.csv


  


  study9_words.csv


  


  study9_s1.csv


  


  study9_s2.csv



  study9_code.R



  study9_output.rdata


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BOX INFORMATION

SUPPLEMENTARY FILES FOR
Adam Morris; Jonathan Phillips; Karen Huang; Fiery Cushman, 'Generating options and choosing between them rely on distinct forms of value representation', Psychological Science

LICENSE FOR USE
All content posted to ResearchBox is under a CC By 4.0 License (all use is allowed as long as authorship of the content is attributed). When using content from ResearchBox please cite the original work, and provide a link to the URL for this box (https://researchbox.org/190).

BOX PUBLIC SINCE
March 04, 2021   (files may not be changed, deleted, or added)

BOX CREATORS
Adam Morris (adam.mtc.morris@gmail.com)
Jonathan Phillips (Jonathan.S.Phillips@dartmouth.edu)
Karen Huang (karen.huang@georgetown.edu)
Fiery Cushman (cushman@fas.harvard.edu)

ABSTRACT
Humans have a remarkable capacity for flexible decision making, deliberating among actions by modeling their likely outcomes. This capacity allows us to adapt to the specific features of diverse circumstances. In real-world decision making, however, people face an important challenge: There are often an enormous number of possibilities to choose among, far too many for exhaustive consideration. There is a crucial, understudied "pre-choice" step in which, among myriad possibilities, a few good candidates come quickly to mind. How do people accomplish this? We show across nine experiments (N = 3972, U.S. residents) that people use computationally-frugal "cached" value estimates to propose a few candidate actions based on their success in past contexts (even when irrelevant for the current context). Deliberative planning is then deployed just within this set, computing more accurate values based on context-specific criteria. This hybrid architecture illuminates how typically-valuable thoughts come quickly to mind during decision making.

'DEAR READER' MESSAGE

The authors have written the following message for visitors to this box.
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Dear Reader,

You must use R version 3 to run the analysis code (I ran it all with R 3.6.3); it will break with R version 4. (Sorry for this annoyance.) An easy way to switch between versions of R can be found here: http://groundhogr.com/many/. Also, the code uses groundhog to ensure reproducibility, but it's kind of finicky; if it fails, just restart your R session a few times and try again.

Studies 1-3 and 8 were made in Qualtrics; the PDF and QSF exports from Qualtrics are included here. (For the Qualtrics data, some of the variable names are sloppy.. E.g. "cs_13" is actually the 8th slot for entering a considered item. Sorry. It should all be clear in the analysis script.) Studies 4-7 and 9 were done in Javascript, using jsPsych. There are three scripts common to all of Studies 4-7 and 9 (utilities.js, savedata.php, and end.php), and then each study has its own index.html. The data for each of Studies 4-7 and 9 are split into four csv files: demographics, stage 1 training, stage 2 test, and month attributes. It should be clear from the codebooks and analysis scripts.

In addition to downloading the materials, you can also go through the experiments yourself with the following links: Pilot, Study 1, Study 2, Study 3, Study 4/5 (short version), Study 6 (short version), Study 7 (short version), Study 8, Study 9 (short version). (The short versions skip most of the long training, so that you can see the whole experiment.) The materials are modified to remove all identifying information, consent forms, database logins, etc.

Note that some analysis scripts (for Studies 1-2 and 4-6) are for multiple studies at once; they include a prompt, asking you which study you want to analyze. A special note for analyzing Study 7: ResearchBox automatically zips the data file "study7_s1.csv" when you download it. So before running "study7_code.R", unzip "study7_s1.csv.zip" and then rename the file that emerges to "study7_s1.csv".

The analysis scripts assume that all the data files are in the same folder; so put them all together before running them.

For the github repo version of this, see: https://github.com/adammmorris/consideration-sets.

For any questions (or if you find any errors), please reach out to me at thatadammorris@gmail.com! :)



This version: March 02, 2021