12,034 rated or chosen profiles from 1,509 respondents, in up to 4 tasks of 2 profiles varying on 5 attributes.
One of 2 tables from the same source; this one is the japan table. The others are listed under Related tables.
| Description | Japanese respondents compared pairs of hypothetical international missions (peacekeeping, diplomatic or humanitarian) varying in personnel, size, lead organisation and location; 1,509 respondents, 4 pairs each. Outcomes are a forced choice and a 1-5 perceived-effectiveness rating of each mission. |
|---|---|
| Reference | Pickering, S. (2025). Replication data for: Peacekeeping by any other name: A conjoint experiment evaluating support for peacekeeping, diplomatic and humanitarian missions in Japan and the UK [Data set]. Harvard Dataverse. |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.7910/DVN/XKSZCU |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,509 |
|---|---|
| Rows (one per respondent, task and profile) | 12,034 |
| Tasks per respondent (most) | 4 |
| Profiles per task | 2 |
| Attributes | 5 |
| Tasks with no profile chosen | 0 |
| Topic | foreign policy security |
|---|---|
| A profile represents | policy |
| Country | JP |
| Language shown | ja |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| choice | unknown [choice, forced] |
|---|---|
| rating | unknown [rating, 1 (Not at all effective) to 5 (Extremely effective)] |
attr_leadattr_locationattr_missionattr_personnelattr_sizechoiceidprofileratingtask
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("pickering_2025_peacekeeping_japan", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("pickering_2025_peacekeeping_japan", source="conj")
@misc{https://doi.org/10.7910/dvn/xkszcu,
doi = {10.7910/DVN/XKSZCU},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/XKSZCU},
author = {Pickering, Steve},
keywords = {Social Sciences},
title = {Replication Data for: Peacekeeping by any other name: A conjoint experiment evaluating support for peacekeeping, diplomatic and humanitarian missions in Japan and the UK},
publisher = {Harvard Dataverse},
year = {2025}
}
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint v4.2 |
| Redivis dataset DOI | 10.57761/qkye-q530 |
| Manifest pin for this IRW version | v4.2 |
| Metadata source | irw_meta v44.0 |