loewen_2019_depression_incumbent_us

1,934 rated or chosen profiles from 967 respondents, in up to 1 tasks of 2 profiles varying on 7 attributes.

One of 4 tables from the same source; this one is the incumbent_us table. The others are listed under Related tables.

About this table

DescriptionUS online respondents (2017, n=967) read one pair of short candidate descriptions: an incumbent (C) vs challenger (D) varying age, gender, race, party and healthcare position, with the incumbent's illness (flu, skin cancer, depression) and voting attendance randomized; chose whom to vote for and who is most prepared, trustworthy and of best character.
ReferenceLoewen, P. J., & Rheault, L. (2021). Voters punish politicians with depression. British Journal of Political Science, 51(1), 427-437.
DOI10.1017/S0007123419000127
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/DHWZYE

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents967
Rows (one per respondent, task and profile)1,934
Tasks per respondent (most)1
Profiles per task2
Attributes7
Tasks with no profile chosen0

Design

Topiccandidate choice
A profile representsperson
CountryUS
Language shownen
Language of stored levelsen
Randomization restrictionsobserved 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 orderinferred from row order
Profile positionrecorded 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:

choiceVote choice between the two candidates (paraphrase) [choice, forced]
choice_characterWhich candidate has the best character? (paraphrase) [choice, forced]
choice_preparedWhich candidate is most prepared? (paraphrase) [choice, forced]
choice_trustWhich candidate is most trustworthy? (paraphrase) [choice, forced]

Columns

attr_ageattr_attendanceattr_genderattr_healthcareattr_illnessattr_partyattr_racechoicechoice_characterchoice_preparedchoice_trustcov_agecov_depression_chancecov_depression_experiencecov_depression_helpcov_depression_prevalencecov_education_codecov_english_firstcov_gender_codecov_party_ididprofiletask

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.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

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_us", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("loewen_2019_depression_incumbent_us", source="conj")

How to cite

@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} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0