chile_2024_safety_vehiclecharacterization

1,885 responses from 24,472 respondents to 13 items.

One of 42 tables from the same source; this one measures Characterization: Vehicle Theft. The others are listed under Related tables.

About this table

DescriptionDetails and circumstances of vehicle theft incidents
ReferenceEncuesta Nacional Urbana de Seguridad Ciudadana (ENUSC)
LicenceCC BY 4.0
Source datahttps://www.ine.gob.cl/estadisticas-por-tema/sociedad-y-condiciones-de-vida/seguridad-ciudadana

Size and shape

Responses1,885
Respondents24,472
Items13
Response categories4
Responses per respondent0.077
Responses per item145
Density0.006
LongitudinalFALSE

Classification

age rangeMixed
sampleRepresentative
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatMixed
primary language(s)spa
construct nameCharacterization: Vehicle Theft

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, chile_2024_safety.do. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.`var'
Respondent covariates
cov_ageCovariate rph_edad
cov_educationCovariate rph_nivel
cov_sexCovariate rph_sexo

What item codes and covariate values stand for is in the source’s codebook, diccionario-de-variables---enusc-2024.xlsx, and its questionnaire, cuestionario-capi---enusc-2024.pdf, which shows the item wording.

Get the data

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

Or load it directly in R or Python:

# R (no account needed)
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("chile_2024_safety_vehiclecharacterization")
# Python (needs a free Redivis account)
pip install irw

import irw
df = irw.fetch("chile_2024_safety_vehiclecharacterization")

How to cite

@misc{ENUSC,
  title = {Encuesta Nacional Urbana de Seguridad Ciudadana (ENUSC)},
  howpublished = {\url{https://www.ine.gob.cl/estadisticas-por-tema/sociedad-y-condiciones-de-vida/seguridad-ciudadana}},
  note = {Accessed: 2023-10-01}
}

Version and provenance

IRW versionv540
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v37.0