1,558 rated or chosen profiles from 779 respondents, in up to 1 tasks of 2 profiles varying on 11 attributes.
One of 4 tables from the same source; this one is the open_ca table. The others are listed under Related tables.
| Description | Canadian online respondents (2017, n=779) read one pair of short candidate descriptions: an open-seat pair of candidates (A, B) varying age, gender, race, occupation, experience, party, abortion, military and tax positions, with Candidate A's health condition (blood pressure, cancer, depression) and leave of absence randomized; chose whom to vote for and who is most prepared, trustworthy and of best character. |
|---|---|
| Reference | Loewen, P. J., & Rheault, L. (2021). Voters punish politicians with depression. British Journal of Political Science, 51(1), 427-437. |
| DOI | 10.1017/S0007123419000127 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/DHWZYE |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 779 |
|---|---|
| Rows (one per respondent, task and profile) | 1,558 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 2 |
| Attributes | 11 |
| Tasks with no profile chosen | 0 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | CA |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | observed in the data (not documented by the source): the two candidates always have opposite parties (every task); health/leave/attendance attributes exist only on the first candidate |
| 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 | Vote choice between the two candidates (paraphrase) [choice, forced] |
|---|---|
| choice_character | Which candidate has the best character? (paraphrase) [choice, forced] |
| choice_prepared | Which candidate is most prepared? (paraphrase) [choice, forced] |
| choice_trust | Which candidate is most trustworthy? (paraphrase) [choice, forced] |
attr_abortionattr_ageattr_experienceattr_genderattr_healthattr_leaveattr_militaryattr_occupationattr_partyattr_raceattr_taxchoicechoice_characterchoice_preparedchoice_trustcov_agecov_born_canadacov_depression_chancecov_depression_experiencecov_depression_helpcov_depression_prevalencecov_education_codecov_gender_codeidprofiletask
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("loewen_2019_depression_open_ca", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("loewen_2019_depression_open_ca", source="conj")
@article{Loewen_2019, title={Voters Punish Politicians with Depression}, volume={51}, ISSN={1469-2112}, url={http://dx.doi.org/10.1017/S0007123419000127}, DOI={10.1017/s0007123419000127}, number={1}, journal={British Journal of Political Science}, publisher={Cambridge University Press (CUP)}, author={Loewen, Peter John and Rheault, Ludovic}, year={2019}, month=Oct, pages={427–436} }
| 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 |