matsuo_2018_uk_policy_packages

11,214 rated or chosen profiles from 1,403 respondents, in up to 4 tasks of 2 profiles varying on 5 attributes.

About this table

DescriptionUK adults (SSI online panel, the week before the 2015 general election) chose between two anonymous parties' policy packages built from the 2015 manifestos (economy, jobs, immigration, EU, education), 4 pairs each. 1,403 respondents, forced choice.
ReferenceMatsuo, A., & Lee, S. (2018). Multi-dimensional policy preferences in the 2015 British general election: A conjoint analysis. Electoral Studies, 55, 89-98.
DOI10.1016/j.electstud.2018.07.005
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/CGHY3L

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

Respondents1,403
Rows (one per respondent, task and profile)11,214
Tasks per respondent (most)4
Profiles per task2
Attributes5
Tasks with no profile chosen0

Design

Topicparties platforms
A profile representspolicy
CountryGB
Language shownen
Language of stored levelsen
Task orderrecorded in the deposit
Profile positioninferred from row order

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

Outcomes:

choiceSuppose that two parties with the issue positions described below had nominated candidates in the general election. Which of these two candidates would you be most likely to vote for? Even if you are not entirely sure, please choose the one that you most prefer. Which candidate would you support? [choice, forced]

Columns

attr_economyattr_educationattr_euattr_immigrationattr_jobschoicecov_country_codecov_education_codecov_pid1_codecov_vote_intentionidprofiletasktrial_time_spend

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("matsuo_2018_uk_policy_packages", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("matsuo_2018_uk_policy_packages", source="conj")

How to cite

@article{Matsuo_2018, title={Multi-dimensional policy preferences in the 2015 British general election: A conjoint analysis}, volume={55}, ISSN={0261-3794}, url={http://dx.doi.org/10.1016/j.electstud.2018.07.005}, DOI={10.1016/j.electstud.2018.07.005}, journal={Electoral Studies}, publisher={Elsevier BV}, author={Matsuo, Akitaka and Lee, Seonghui}, year={2018}, month=Oct, pages={89–98} }

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