pan_2025_diplomatic_visits

22,450 rated or chosen profiles from 2,245 respondents, in up to 5 tasks of 2 profiles varying on 6 attributes.

About this table

DescriptionTaiwanese respondents (n = 2,245) each saw 5 pairs of hypothetical politicians with randomized gender, party, education, past meetings with senior Chinese and US officials and stance on the 1992 Consensus, and chose which (if either) they preferred as a defender of national security.
ReferencePan, H.-H., & Kagotani, K. (forthcoming). Diplomatic visits and image-building: A conjoint analysis in Taiwan. Asian Survey.
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/HMRB9N

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

Respondents2,245
Rows (one per respondent, task and profile)22,450
Tasks per respondent (most)5
Profiles per task2
Attributes6
Tasks with no profile chosen5,105

Design

Topiccandidate choice
A profile representsperson
CountryTW
Language shownzh
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceWhich of these two politicians would you prefer as a defender of Taiwan's national security? (paraphrase) [choice, opt-out allowed]

Columns

attr_cross_strait_policyattr_educationattr_genderattr_met_china_officialsattr_met_us_officialsattr_partychoicecov_born_before_1978cov_collegecov_cross_strait_relationscov_gendercov_residencecov_us_taiwan_relationsidprofiletask

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("pan_2025_diplomatic_visits", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("pan_2025_diplomatic_visits", source="conj")

How to cite

@misc{https://doi.org/10.7910/dvn/hmrb9n,
  doi = {10.7910/DVN/HMRB9N},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/HMRB9N},
  author = {Pan, Hsin-Hsin and Kagotani, Koji},
  keywords = {Social Sciences, Taiwan, diplomatic visits, national security, image-building, conjoint analysis},
  title = {Replication Data for: Diplomatic Visits and Image-Building: A Conjoint Analysis in Taiwan},
  publisher = {Harvard Dataverse},
  year = {2025}
}

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0