26 Aug test
This document describes the labels and content of variables in the data.
Codebook for Choice Data
Metadata
Description
Dataset name: Human risky choices with goals
Repeated binary choices by adult humans among a high- and a low-variance two-outcome lottery, who were given a point goal to reach after a certain number of choices
Metadata for search engines
- Temporal Coverage: Dec 2018 – Jan 2019
- Spatial Coverage: online
-
Citation: Jarecki, J. B., & Rieskamp, J. (2020). Prospect Theory and Optimal Risky Choices with Goals.
-
Date published: 2020-08-26
-
Creator:
name | value |
---|---|
@type | Person |
givenName | Jana B. |
familyName | Jarecki |
jj@janajarecki.com | |
affiliation | Organization , University of Basel, Switzerland |
|x | |
|x | |
|x | |
Codebook table
JSON-LD metadata
The following JSON-LD can be found by search engines, if you share this codebook
publicly on the web.
{
"citation": "Jarecki, J. B., & Rieskamp, J. (2020). Prospect Theory and Optimal Risky Choices with Goals.",
"creator": {
"@type": "Person",
"givenName": "Jana B.",
"familyName": "Jarecki",
"email": "jj@janajarecki.com",
"affiliation": {
"@type": "Organization",
"name": "University of Basel, Switzerland"
}
},
"spatialCoverage": "online",
"temporalCoverage": "Dec 2018 - Jan 2019",
"measurementTechnique": "Incentivized online choice task",
"funder": "Center for Economic Psychology, University of Basel",
"keywords": ["online study", "risky choice", "risky gamble", "risk-sensitive foraging", "risk sensitivity", "risk sensitive foraging", "energy budget rule", "decisions under quota", "psychology", "Prolific Academic", "cognition", "cognitive modeling"],
"description": "Repeated binary choices by adult humans among a high- and a low-variance two-outcome lottery, who were given a point goal to reach after a certain number of choices\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
"name": "Human risky choices with goals",
"datePublished": "2020-08-26",
"@context": "http://schema.org/",
"@type": "Dataset",
"variableMeasured": [
{
"name": "id",
"description": "Participant id, after excluding participants",
"@type": "propertyValue"
},
{
"name": "phase",
"description": "Phase of the experiment",
"value": "1. familiarize,\n2. five,\n3. one",
"@type": "propertyValue"
},
{
"name": "block",
"description": "Block number in a phase: 1 in familiarization, 7 in five-trial phase, 1 in one-shot phase.",
"@type": "propertyValue"
},
{
"name": "round",
"description": "Round number, consecutive number, independent of block or phase.",
"@type": "propertyValue"
},
{
"name": "trial",
"description": "Trial number in a round",
"@type": "propertyValue"
},
{
"name": "state",
"description": "Number of points accumulated until this trial",
"@type": "propertyValue"
},
{
"name": "budget",
"description": "Point requirement in this round",
"@type": "propertyValue"
},
{
"name": "stimulus0",
"description": "Describes the first option (risky gamble) in this round in xpy notation: firstOutcome_prFirst_secondOutcome",
"@type": "propertyValue"
},
{
"name": "stimulus1",
"description": "Describes the second option (risky gamble) in this round in xpy notation: firstOutcome_prFirst_secondOutcome",
"@type": "propertyValue"
},
{
"name": "terminal_state",
"description": "Total points by the end of this round",
"@type": "propertyValue"
},
{
"name": "choice_1isHighVar",
"description": "Choice in this trial",
"value": "0. Low-variance option,\n1. High-variance option",
"maxValue": 1,
"minValue": 0,
"@type": "propertyValue"
},
{
"name": "success",
"description": "Did the terminal_state (total points) exceed the budget (requirement) by the end of this round?",
"value": "0. No,\n1. Yes",
"maxValue": 1,
"minValue": 0,
"@type": "propertyValue"
},
{
"name": "successes",
"description": "Number of rounds with a success up to this round",
"@type": "propertyValue"
},
{
"name": "rt_ms",
"description": "Reaction time in this trial in milliseconds",
"@type": "propertyValue"
},
{
"name": "xh",
"description": "Outcome of the high-variance option in this round",
"@type": "propertyValue"
},
{
"name": "ph",
"description": "Probability of x_h",
"@type": "propertyValue"
},
{
"name": "yh",
"description": "Second outcome of high-variance option, pr(y_h) = 1 - p_h",
"@type": "propertyValue"
},
{
"name": "xl",
"description": "Outcome of the low-variance option in this round",
"@type": "propertyValue"
},
{
"name": "pl",
"description": "Probability of x_l",
"@type": "propertyValue"
},
{
"name": "yl",
"description": "Second outcome of low-variance option, pr(y_l) = 1 - p_l",
"@type": "propertyValue"
},
{
"name": "gneezy_potter",
"description": "One-shot choice (asked once after the choice phase): Which part of the 100 pennys do you wish to invest in the lottery? With probability 67% the lottery pays zero. You earn the amount that you did not invest. With probability 33% the lottery pays 2.5X. You earn +2.5 x X plus the amount that you did not invest.",
"@type": "propertyValue"
},
{
"name": "layout_featurecolor",
"description": "Which feature is shown in which color in this round. The colors are dark grey (RGB #D9D9D9, grey85) or light grey (RGB #737373, gray45)",
"value": "1. Outcome x colored dark,\n2. Outcome x colored light",
"@type": "propertyValue"
},
{
"name": "layout_stimulusposition_01",
"description": "In which order stimulus0 and stimulus 1 are shown in this round (left or right on screen)",
"value": "1. stimulus0 shown left,\n2. stimulus1 shown left",
"@type": "propertyValue"
}
]
}`
Codebook for Demographic Data
Metadata
Description
Dataset name: results
The dataset has N=60 rows and 17 columns.
0 rows have no missing values on any column.
Metadata for search engines
- Temporal Coverage: Dec 2018 – Jan 2019
- Spatial Coverage: online
-
Citation: Jarecki, J. B., & Rieskamp, J. (2020). Prospect Theory and Optimal Risky Choices with Goals.
-
Date published: 2020-08-26
-
Creator:
name | value |
---|---|
@type | Person |
givenName | Jana B. |
familyName | Jarecki |
jj@janajarecki.com | |
affiliation | Organization , University of Basel, Switzerland |
|x | |
|x | |
|x | |
Codebook table
<!–html_preserve–>
JSON-LD metadata
The following JSON-LD can be found by search engines, if you share this codebook
publicly on the web.
{
"citation": "Jarecki, J. B., & Rieskamp, J. (2020). Prospect Theory and Optimal Risky Choices with Goals.",
"creator": {
"@type": "Person",
"givenName": "Jana B.",
"familyName": "Jarecki",
"email": "jj@janajarecki.com",
"affiliation": {
"@type": "Organization",
"name": "University of Basel, Switzerland"
}
},
"spatialCoverage": "online",
"temporalCoverage": "Dec 2018 - Jan 2019",
"measurementTechnique": "Incentivized online choice task",
"funder": "Center for Economic Psychology, University of Basel",
"keywords": ["online study", "risky choice", "risky gamble", "risk-sensitive foraging", "risk sensitivity", "risk sensitive foraging", "energy budget rule", "decisions under quota", "psychology", "Prolific Academic", "cognition", "cognitive modeling"],
"name": "results",
"datePublished": "2020-08-26",
"description": "The dataset has N=60 rows and 17 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n|name |label | n_missing|\n|:---------------------|:------------------------------------------------------------------------------------------|---------:|\n|id |Participant id | 0|\n|age |How old are you? | 0|\n|gender |NA | 0|\n|language_english |NA | 0|\n|dataquality |Is the data you just generated of sufficient quality to be useful for scientific research? | 0|\n|income |Which category does your monthly income after tax fall into? | 0|\n|strategy |Can you describe how you made the decision which of the two options to pick? | 0|\n|task_clear |Was it clear to you what your task was during this study? | 0|\n|open_text |Is there anything you would like us to know? | 0|\n|created |Time started UTC | 0|\n|ended |Time ended UTC | 0|\n|excl |If participant is excluded, the reason for exclusion | 0|\n|bonus_riskychoice_GBP |Bonus from 5 risky choice rounds in British Pounds | 0|\n|bonus_gneezy_GBP |Bonus from Gneezy & Potter task in British Pounds | 0|\n|session |NA | 0|\n|modified |NA | 0|\n|expired |NA | 60|\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
"@context": "http://schema.org/",
"@type": "Dataset",
"variableMeasured": [
{
"name": "id",
"description": "Participant id",
"@type": "propertyValue"
},
{
"name": "age",
"description": "How old are you?",
"@type": "propertyValue"
},
{
"name": "gender",
"value": "1. Female,\n2. Male,\n3. Prefer not to state",
"@type": "propertyValue"
},
{
"name": "language_english",
"value": "1. No,\n2. Yes",
"@type": "propertyValue"
},
{
"name": "dataquality",
"description": "Is the data you just generated of sufficient quality to be useful for scientific research?",
"value": "0. Not useful at all,\n1. Partly useful,\n2. Mostly useful,\n3. Completely useful",
"maxValue": 3,
"minValue": 0,
"@type": "propertyValue"
},
{
"name": "income",
"description": "Which category does your monthly income after tax fall into?",
"value": "0. up to 1000,\n1. 1001 - 2000,\n2. 2001 - 3000,\n3. 3001 - 4000,\n4. 4001 - or more,\n99. Do not want to answer",
"maxValue": 99,
"minValue": 0,
"@type": "propertyValue"
},
{
"name": "strategy",
"description": "Can you describe how you made the decision which of the two options to pick?",
"@type": "propertyValue"
},
{
"name": "task_clear",
"description": "Was it clear to you what your task was during this study?",
"value": "0. Not clear,\n1. Mostly not clear,\n2. Mostly clear,\n3. Completely clear",
"maxValue": 3,
"minValue": 0,
"@type": "propertyValue"
},
{
"name": "open_text",
"description": "Is there anything you would like us to know?",
"@type": "propertyValue"
},
{
"name": "created",
"description": "Time started UTC",
"@type": "propertyValue"
},
{
"name": "ended",
"description": "Time ended UTC",
"@type": "propertyValue"
},
{
"name": "excl",
"description": "If participant is excluded, the reason for exclusion",
"value": ". Included,\nany non-empty value. Excluded",
"maxValue": "any non-empty value",
"minValue": "",
"@type": "propertyValue"
},
{
"name": "bonus_riskychoice_GBP",
"description": "Bonus from 5 risky choice rounds in British Pounds",
"@type": "propertyValue"
},
{
"name": "bonus_gneezy_GBP",
"description": "Bonus from Gneezy & Potter task in British Pounds",
"@type": "propertyValue"
},
{
"name": "session",
"@type": "propertyValue"
},
{
"name": "modified",
"@type": "propertyValue"
},
{
"name": "expired",
"@type": "propertyValue"
}
]
}`