38,222 rated or chosen profiles from 2,404 respondents, in up to 8 tasks of 2 profiles varying on 9 attributes.
One of 2 tables from the same source; this one is the mar22 table. The others are listed under Related tables.
| Description | Paired conjoint in which 2,404 Japanese adults (Rakuten Insight, March 2022) compared hypothetical candidates for the House of Representatives or (random half) a municipal council, varying in gender, party, age, experience, education, family, birthplace, residence and policy focus; four tasks asked which is more desirable and four which is more likely to be elected. Outcomes: choice, choice_expect. |
|---|---|
| Reference | Kato, G., Lu, F., & Endo, M. (2025). The preference-expectation gap in support for female candidates: Evidence from Japan. Public Opinion Quarterly, 89(1), 217-228. |
| DOI | 10.1093/poq/nfaf002 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/GJWDVM |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,404 |
|---|---|
| Rows (one per respondent, task and profile) | 38,222 |
| Tasks per respondent (most) | 8 |
| Profiles per task | 2 |
| Attributes | 9 |
| Tasks with no profile chosen | 0 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | JP |
| Language shown | ja |
| Language of stored levels | en |
| Randomization restrictions | observed in the data (not documented by the source): No profile pairs age '35 Years Old' with experience 'Incumbent (5 terms)'; as a result age 35 (21%) and 5 terms (16%) are less frequent than the other levels. |
| Task order | inferred from row order |
| Profile position | recorded in the deposit |
Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead. Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| choice | Which of the following two persons do you think is more desirable as a Single Member District member of the House of Representatives [Municipal Council in the municipal arm]? Even if you are not entirely sure, please indicate which of the two you would think is more desirable. (translated) [choice, forced] |
|---|---|
| choice_expect | Which of the following two persons do you think is more likely to be elected in a Single Member District election of the House of Representatives [Municipal Council in the municipal arm]? Even if you are not entirely sure, please indicate which of the two you would think is more likely to be elected. (translated) [choice, forced] |
attr_ageattr_educationattr_experienceattr_familyattr_genderattr_originattr_partyattr_policy_focusattr_residenceattrpos_ageattrpos_educationattrpos_experienceattrpos_familyattrpos_genderattrpos_originattrpos_partyattrpos_policy_focusattrpos_residencechoicechoice_expectcov_gendercov_genderval_1cov_genderval_2cov_genderval_3cov_genderval_4cov_genderval_5cov_genderval_6cov_genderval_7cov_genderval_8cov_genderval_9idprofiletasktrial_block_ordertrial_election_level
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("kato_2025_candidates_mar22", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("kato_2025_candidates_mar22", source="conj")
@article{Kato_2025, title={The Preference-Expectation Gap in Support for Female Candidates: Evidence from Japan}, volume={89}, ISSN={1537-5331}, url={http://dx.doi.org/10.1093/poq/nfaf002}, DOI={10.1093/poq/nfaf002}, number={1}, journal={Public Opinion Quarterly}, publisher={Oxford University Press (OUP)}, author={Kato, Gento and Lu, Fan and Endo, Masahisa}, year={2025}, pages={217–228} }
| 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 |