1,558 rated or chosen profiles from 779 respondents, in up to 1 tasks of 2 profiles varying on 9 attributes.
One of 4 tables from the same source; this one is the incumbent_ca table. The others are listed under Related tables.
| Description | Canadian online respondents (2017, n=779) read one pair of short candidate descriptions: an incumbent (C) vs challenger (D) varying age, gender, race, occupation, party and daycare position, with the incumbent's illness (flu, skin cancer, depression) and voting attendance randomized, and a challenger military sentence; 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 | 9 |
| 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 and the military sentence only on D |
| 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_ageattr_attendanceattr_daycareattr_genderattr_illnessattr_militaryattr_occupationattr_partyattr_racechoicechoice_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_incumbent_ca", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("loewen_2019_depression_incumbent_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 |