lopezgarcia_2023_mx_military_proposal

2,401 rated or chosen profiles from 2,401 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.

One of 3 tables from the same source; this one is the military_proposal table. The others are listed under Related tables.

About this table

Description2,401 Mexican online respondents read a proposal to take the military off the streets whose proposing party (PAN or PRI, or none named) and partner (municipal authorities, private sector, citizens, or none named) were randomized; outcome: 1-5 agreement.
ReferenceLópez García, A. I., Berens, S., & Maydom, B. (2023). MigCrimeMexSurvey 2021 [Data set]. Harvard Dataverse.
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/dvn/byavmc

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

Respondents2,401
Rows (one per respondent, task and profile)2,401
Tasks per respondent (most)1
Profiles per task1
Attributes2

Design

Topiccrime justice policing
A profile representspolicy
CountryMX
Language shownes
Language of stored levelsen
Randomization restrictionsunknown
Task orderinferred from row order
Profile positioninferred from row order

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

Outcomes:

rating_agreeOn a scale from 1 to 5, where 1 means strongly disagree and 5 means strongly agree, to what extent do you agree or disagree with this proposal? [rating, 1 (Strongly disagree) to 5 (Strongly agree)]

Columns

attr_collaborationattr_proposing_partycov_agecov_age_groupcov_educationcov_gendercov_stateidprofilerating_agreetask

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("lopezgarcia_2023_mx_military_proposal", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("lopezgarcia_2023_mx_military_proposal", source="conj")

How to cite

@misc{https://doi.org/10.7910/dvn/byavmc,
  doi = {10.7910/DVN/BYAVMC},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/BYAVMC},
  author = {Lopez Garcia, Ana Isabel and Berens, Sarah and Maydom, Barry},
  keywords = {Social Sciences},
  title = {Replication Data for: Emigration, Social Remittances and Fiscal Policy Preferences: Experimental Evidence from Mexico.},
  publisher = {Harvard Dataverse},
  year = {2023}
}

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