12,008 rated or chosen profiles from 1,203 respondents, in up to 5 tasks of 2 profiles varying on 6 attributes.

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

About this table

Description	1,203 US respondents from an MTurk convenience sample each judged up to 5 hypothetical (mayoral) elections between two candidates described by race, gender, age, political experience, career experience and, in randomly chosen partisan elections only, party; outcomes are a forced choice and a 0-100 competence rating of each candidate.
Reference	Kirkland, P. A., & Coppock, A. (2018). Candidate choice without party labels: New insights from conjoint survey experiments. Political Behavior, 40(3), 571-591.
DOI	10.1007/s11109-017-9414-8
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/WSUHI3

Notes

Conjoint table (irw_conjoint). choice = 'Which of these two candidates do you prefer?' (forced choice, no opt-out); rating = 'On a scale from 0 to 100, how competent do you think these candidates would be as mayor?' (0-100, higher = more competent). Attributes fully randomized; whether party is shown is randomized per election (trial_election; attr_party = '(not shown)' when not shown). Profile order is inferred from row order; attribute order was randomized and not recorded. MTurk worker ID dropped and respondents re-keyed; one worker with two sets of contests and 4 contests left with one row by the authors' na.omit dropped.

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

Size and shape

Respondents	1,203
Rows (one per respondent, task and profile)	12,008
Tasks per respondent (most)	5
Profiles per task	2
Attributes	6
Tasks with no profile chosen	0

Design

Topic	candidate choice
A profile represents	person
Country	US
Language shown	en
Language of stored levels	en
Task order	recorded in the deposit
Profile position	inferred from row order

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

choice	Which of these two candidates do you prefer? [choice, forced]
rating	On a scale from 0 to 100, how competent do you think these candidates would be as mayor? [rating, 0 (unknown) to 100 (unknown)]

Columns

attr_ageattr_genderattr_jobattr_partyattr_politicalattr_racechoicecov_party_idcov_party_id7_codeidprofileratingtasktrial_election

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 needed Browse on Redivisexplore and query Croissant 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("kirkland_2018_candidates_mturk", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("kirkland_2018_candidates_mturk", source="conj")

How to cite

@article{Kirkland_2017, title={Candidate Choice Without Party Labels:: New Insights from Conjoint Survey Experiments}, volume={40}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-017-9414-8}, DOI={10.1007/s11109-017-9414-8}, number={3}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Kirkland, Patricia A. and Coppock, Alexander}, year={2017}, month=June, pages={571–591} }

Version and provenance

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