garciaramirez_2025_crossing_noncompliant

8,694 rated or chosen profiles from 483 respondents, in up to 6 tasks of 3 profiles varying on 5 attributes.

One of 2 tables from the same source; this one is the noncompliant table. The others are listed under Related tables.

About this table

DescriptionVisual discrete choice experiment on pedestrian crossing in Ecuador (Experiment 1, images of non-compliant pedestrian behaviour): 483 respondents chose among a pedestrian bridge, a direct crossing and a signalised intersection in each of six fixed scenarios that varied trip delay, accompanying minor, vehicle flow and extra distance.
ReferenceGarcia-Ramirez, Y. (2025). Dataset and R script for visual discrete choice experiments on pedestrian crossing behavior in Ecuador [Data set]. Zenodo.
LicenceCC BY 4.0
Source datahttps://doi.org/10.5281/zenodo.17794518

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents483
Rows (one per respondent, task and profile)8,694
Tasks per respondent (most)6
Profiles per task3
Attributes5
Tasks with no profile chosen0

Design

Topicclimate energy environment
A profile representsscenario
CountryEC
Language shownes
Language of stored levelses
Task orderinferred from row order
Profile positionrecorded in the deposit

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

choiceWhich crossing would you choose in this situation: 1. Puente peatonal, 2. Cruce directo, 3. Intersección semaforizada? (paraphrase) [choice, forced]

Columns

attr_additional_distanceattr_crossing_typeattr_minor_accompanyingattr_trip_delayattr_vehicle_flowchoicecov_agecov_drivers_licencecov_educationcov_gendercov_household_incomecov_household_vehiclecov_provinceidprofiletask

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("garciaramirez_2025_crossing_noncompliant", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("garciaramirez_2025_crossing_noncompliant", source="conj")

How to cite

@misc{https://doi.org/10.5281/zenodo.17794518,
  doi = {10.5281/ZENODO.17794518},
  url = {https://zenodo.org/doi/10.5281/zenodo.17794518},
  author = {García_Ramírez, Yasmany},
  title = {Dataset and R Script for Visual Discrete Choice Experiments on Pedestrian Crossing Behavior in Ecuador},
  publisher = {Zenodo},
  year = {2025},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint_2 v1.4
Redivis dataset DOI10.57761/hk97-wv30
Manifest pin for this IRW versionv1.4
Metadata sourceirw_meta v44.0