3,386 rated or chosen profiles from 573 respondents, in up to 3 tasks of 2 profiles varying on 5 attributes.
| Description | Conjoint among 573 US local elected officials, who rated two hypothetical pieces of constituent feedback on each of three local issues (park, retail development, school tax), varying mode (office visit vs social media), number of constituents, who they were, the type of argument and the position; outcomes are 1-4 ratings of how informative and how influential each message is. |
|---|---|
| Reference | Lee, N. R., Chen, K., Marble, W., & Bram, C. (2025). Voice and value: How elected officials evaluate online and offline constituent feedback. Public Opinion Quarterly, 89(1), 31-48. |
| DOI | 10.1093/poq/nfaf006 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/VU01FS |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 573 |
|---|---|
| Rows (one per respondent, task and profile) | 3,386 |
| Tasks per respondent (most) | 3 |
| Profiles per task | 2 |
| Attributes | 5 |
| Topic | public administration |
|---|---|
| A profile represents | message |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | yes (stated by the source): constituent types (3 per issue) and arguments (3 per issue x position) are drawn from issue-specific lists; the support/oppose position is the same for both messages of an issue (holds for every respondent) |
| Task order | unknown |
| 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.
Outcomes:
| rating_influential | How influential would this feedback be on your decision? (paraphrase) [rating, 1 (Not influential) to 4 (Very influential)] |
|---|---|
| rating_informative | How informative is this feedback? (paraphrase) [rating, 1 (Not informative) to 4 (Very informative)] |
attr_argumentattr_constituentsattr_modeattr_numberattr_positioncov_agecov_educationcov_gendercov_gov_expcov_job_expcov_party_idcov_progresscov_salaryidprofilerating_influentialrating_informativetasktrial_info_firsttrial_issue
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("lee_2025_constituent_feedback", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("lee_2025_constituent_feedback", source="conj")
@article{Lee_2025, title={Voice and Value: How Elected Officials Evaluate Online and Offline Constituent Feedback}, volume={89}, ISSN={1537-5331}, url={http://dx.doi.org/10.1093/poq/nfaf006}, DOI={10.1093/poq/nfaf006}, number={1}, journal={Public Opinion Quarterly}, publisher={Oxford University Press (OUP)}, author={Lee, Nathan and Chen, Kaiping and Marble, William and Bram, Curtis}, year={2025}, pages={31–48} }
| 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 |