sun_2016_risky_choice_graph
756 responses from 189 respondents to 4 items.
About this table
| Description | 4-item binary risky-choice task (probability-bet vs money-bet gamble pairs, resp 1/0), undergraduate decision-making study on graph-scale display effects |
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| Reference | Sun Y, et al. (2016) Effect of Graph Scale on Risky Choice: Evidence from Preference and Process in Decision-Making. PLoS ONE. |
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| DOI | 10.1371/journal.pone.0146914 |
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| Licence | CC BY 4.0 |
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| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0146914.s001 |
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Size and shape
| Responses | 756 |
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| Respondents | 189 |
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| Items | 4 |
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| Response categories | 2 |
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| Responses per respondent | 4 |
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| Responses per item | 189 |
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| Density | 1 |
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| Longitudinal | FALSE |
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Classification
| sample | Educational |
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| measurement tool | Test |
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| item format | Likert Scale/selected response |
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| primary language(s) | chi |
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Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Graph-scale risky choice task, Experiment 1 (Sun et al., 2016): four probability-bet vs money-bet pairs |
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| Mean words per item | 1 |
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| Mean characters per item | 2 |
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| Mean characters per response | 9.625 |
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| Flesch-Kincaid grade level | -3.400 |
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Columns
cov_graph_conditioniditemresp
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("sun_2016_risky_choice_graph")
# Python
pip install irw
import irw
df = irw.fetch("sun_2016_risky_choice_graph")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_4 v7.0 |
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| Redivis dataset DOI | 10.57761/cpj5-vm97 |
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| Manifest pin for this IRW version | v7.0 |
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| Metadata source | irw_meta v23.0 |
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