29,484 rated or chosen profiles from 1,638 respondents, in up to 9 tasks of 2 profiles varying on 4 attributes.
| Description | US online respondents (August 2023) chose between two hypothetical Medicare-based health-insurance programs in 9 pairs, varying the transition from private insurance, who benefits most, who bears the tax burden, and total cost. 1,638 respondents; forced binary choice. |
|---|---|
| Reference | Qi, H. (2025). Understanding public attitudes toward redistribution: Analysis by ideological subgroups. Public Opinion Quarterly. |
| DOI | 10.1093/poq/nfaf046 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/ABP4XA |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,638 |
|---|---|
| Rows (one per respondent, task and profile) | 29,484 |
| Tasks per respondent (most) | 9 |
| Profiles per task | 2 |
| Attributes | 4 |
| Tasks with no profile chosen | 0 |
| Topic | health covid, tax welfare economy |
|---|---|
| A profile represents | policy |
| Country | US |
| Language shown | en |
| 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:
| choice | Which of the two programs do you prefer? (paraphrase) [choice, forced] |
|---|
attr_costattr_distributionattr_tax_burdenattr_transitionchoicecov_agecov_age_groupcov_attention_pass_1cov_attention_pass_2cov_attention_pass_3cov_attention_pass_4cov_duration_seccov_educationcov_employmentcov_gendercov_ideologycov_incomecov_party_idcov_party_id7cov_political_attentioncov_racecov_screener_countidprofiletask
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("qi_2025_health_redistribution", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("qi_2025_health_redistribution", source="conj")
@article{Qi_2025, title={Understanding Public Attitudes Toward Redistribution: Analysis by Ideological Subgroups}, volume={89}, ISSN={1537-5331}, url={http://dx.doi.org/10.1093/poq/nfaf046}, DOI={10.1093/poq/nfaf046}, number={3}, journal={Public Opinion Quarterly}, publisher={Oxford University Press (OUP)}, author={Qi, Hang}, year={2025}, pages={902–914} }
| IRW version | v607 |
|---|---|
| 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 v47.0 |