neuner_2022_populist_candidates_2017

23,710 rated or chosen profiles from 2,371 respondents, in up to 5 tasks of 2 profiles varying on 6 attributes.

One of 3 tables from the same source; this one is the candidates_2017 table. The others are listed under Related tables.

About this table

DescriptionGerman voting-eligible adults from the Payback Online Panel, 2017 (third panel wave, n=2,371), chose between 5 pairs of fictitious candidates without party labels, varying positions on refugees, the EU, taxes on the rich and free trade and a first and second policy priority. Outcome: which candidate they would rather vote for.
ReferenceNeuner, F. G., & Wratil, C. (2022). The populist marketplace: Unpacking the role of "thin" and "thick" ideology. Political Behavior, 44(2), 551-574.
DOI10.1007/s11109-020-09629-y
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/Z66XXP

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

Respondents2,371
Rows (one per respondent, task and profile)23,710
Tasks per respondent (most)5
Profiles per task2
Attributes6
Tasks with no profile chosen0

Design

Topiccandidate choice
A profile representsperson
CountryDE
Language shownde
Language of stored levelsde
Randomization restrictionsyes (stated by the source): first and second priority drawn from the same list and cannot be identical
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:

choiceWhich candidate in each pair would you rather cast your vote for? (paraphrase) [choice, forced]

Columns

attr_euattr_priority_firstattr_priority_secondattr_refugeesattr_taxesattr_tradechoicecov_eu_membershipcov_eu_unificationcov_globalizationcov_immigrantscov_refugees_warcov_survey_weightcov_tax_richcov_thin_pop_1cov_thin_pop_2cov_thin_pop_3cov_thin_pop_4cov_thin_pop_5cov_thin_pop_6cov_thin_pop_7cov_thin_pop_8cov_vote_intentionidprofiletask

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("neuner_2022_populist_candidates_2017", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("neuner_2022_populist_candidates_2017", source="conj")

How to cite

@article{Neuner_2020, title={The Populist Marketplace: Unpacking the Role of “Thin” and “Thick” Ideology}, volume={44}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-020-09629-y}, DOI={10.1007/s11109-020-09629-y}, number={2}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Neuner, Fabian G. and Wratil, Christopher}, year={2020}, month=July, pages={551–574} }

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