3,999 rated or chosen profiles from 1,000 respondents, in up to 4 tasks of 1 profile varying on 8 attributes.
| Description | US adults in the CCES 2014 Yale team module (YouGov, pre-election wave; n = 1,000) each saw four randomly generated candidate profiles (gender, family, religion, military service, job, top three issue priorities) and guessed the candidate's party, said how sure they were, and rated the candidate 0-10. |
|---|---|
| Reference | Henderson, J. (2017). CCES 2014, Team Module of Yale University (JAH) [Data set]. Harvard Dataverse. |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/WL6VCW |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,000 |
|---|---|
| Rows (one per respondent, task and profile) | 3,999 |
| Tasks per respondent (most) | 4 |
| Profiles per task | 1 |
| Attributes | 8 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | observed in the data (not documented by the source): the three issue priorities of a profile are always three different issues (no repeats in 3,999 profiles); no source documents the rule |
| Task order | recorded in the deposit |
| 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 | How favorably or unfavorably do you feel toward this candidate? Neither Unfavorable nor Favorable [rating, 0 (Very Unfavorable) to 10 (Very Favorable)] |
|---|---|
| rating_party | If you had to guess, do you think this candidate is a Democrat or Republican? [rating, 1 (Democrat) to 2 (Republican)] |
| rating_sure | How sure are you about the candidate's party? [rating, 1 (Very sure) to 4 (Very unsure)] |
attr_familyattr_genderattr_issue1attr_issue2attr_issue3attr_jobattr_militaryattr_religioncov_birth_yearcov_educationcov_gendercov_party_idcov_party_id7cov_racecov_survey_weightidprofileratingrating_partyrating_suretask
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("henderson_2014_party_guess", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("henderson_2014_party_guess", source="conj")
@misc{https://doi.org/10.7910/dvn/wl6vcw,
doi = {10.7910/DVN/WL6VCW},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/WL6VCW},
author = {Henderson, John},
keywords = {Social Sciences, Political Ads, Policy Issues, Race, 2014 Election, Survey, Voting, Congress, Public Opinion, Attack Ads, Campaigning, Partisanship, Positive Ads, Democrats, Republicans, Family Policy, Immigration, Veterans, Healthcare, Candidates, Patriotism, Unions, Economy, Taxes, Minority, News, Constituency, Gay Marriage, Abortion, Ideology, Party Guessing Experiments, Candidate Vignettes, Seniority, Co-ethnic Candidates, Conjoint Experiments},
title = {CCES 2014, Team Module of Yale University (JAH)},
publisher = {Harvard Dataverse},
year = {2017}
}
| 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 |