lublin_2023_candidate_pairs

25,030 rated or chosen profiles from 2,503 respondents, in up to 5 tasks of 2 profiles varying on 7 attributes.

One of 2 tables from the same source; this one is the pairs table. The others are listed under Related tables.

About this table

Description2,503 US adults (quota online sample, 2021) compared five pairs of hypothetical US congressional candidates described by ethnicity, career, gender, incumbency, prior elected office, party and political views; they chose one candidate or 'no preference'.
ReferenceLublin, D., & Wright, M. (2023). Diversity matters: The election of Asian Americans to U.S. state and federal legislatures. American Political Science Review.
DOI10.1017/s0003055423000242
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/dvn/nyoxte

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

Respondents2,503
Rows (one per respondent, task and profile)25,030
Tasks per respondent (most)5
Profiles per task2
Attributes7
Tasks with no profile chosen1,959

Design

Topiccandidate choice
A profile representsperson
CountryUS
Language shownen
Language of stored levelsen
Randomization restrictionsyes (stated by the source): observed: every pair has one Democrat and one Republican and one incumbent and one challenger; political views never pair Liberal-Liberal or Conservative-Conservative; ethnicity is drawn conditionally on the respondent's group (as in the vignette), so level shares depend on the respondent
Task orderrecorded in the deposit
Profile positioninferred from row order

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:

choiceNow, imagine that the two candidates below are running against each other ... (paraphrase; truncated variable label QCANDPREFA) [choice, opt-out allowed]

Columns

attr_careerattr_ethnicityattr_genderattr_incumbencyattr_partyattr_political_viewsattr_prior_elected_officechoicecov_agecov_asian_origincov_educationcov_gendercov_party_id7cov_respondent_ethnicityidprofiletask

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("lublin_2023_candidate_pairs", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("lublin_2023_candidate_pairs", source="conj")

How to cite

@article{LUBLIN_2023, title={Diversity Matters: The Election of Asian Americans to U.S. State and Federal Legislatures}, volume={118}, ISSN={1537-5943}, url={http://dx.doi.org/10.1017/s0003055423000242}, DOI={10.1017/s0003055423000242}, number={1}, journal={American Political Science Review}, publisher={Cambridge University Press (CUP)}, author={LUBLIN, DAVID and WRIGHT, MATTHEW}, year={2023}, month=Mar, pages={380–400} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint_2 v1.4
Redivis dataset DOI10.57761/hk97-wv30
Manifest pin for this IRW versionv1.4
Metadata sourceirw_meta v44.0