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 security_officers table. The others are listed under Related tables.
| Description | 2,401 Mexican online respondents rated a statement that more security officers are needed to reduce crime, with the place (most violent municipalities, or none named) and a complementary programme (five options, or none) randomized; outcome: 1-5 agreement. |
|---|---|
| Reference | López García, A. I., Berens, S., & Maydom, B. (2023). MigCrimeMexSurvey 2021 [Data set]. Harvard Dataverse. |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/dvn/byavmc |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,401 |
|---|---|
| Rows (one per respondent, task and profile) | 2,401 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 2 |
| Topic | crime justice policing |
|---|---|
| A profile represents | policy |
| Country | MX |
| Language shown | es |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | inferred from row order |
| Profile position | inferred 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_agree | To what extent do you agree or disagree with the following statement? 'To reduce and control crime <place>, it is necessary to have more security officers on the streets <programme>' [rating, 1 (Strongly disagree) to 5 (Strongly agree)] |
|---|
attr_placeattr_programmecov_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.
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_security_officers", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("lopezgarcia_2023_mx_security_officers", source="conj")
@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}
}
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint_2 v1.4 |
| Redivis dataset DOI | 10.57761/hk97-wv30 |
| Manifest pin for this IRW version | v1.4 |
| Metadata source | irw_meta v44.0 |