mader_2024_eu_military_costs

36,452 rated or chosen profiles from 36,452 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.

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

About this table

DescriptionRespondents in 25 EU countries (n = 36,452 with an answer of 40,500) read about an EU military intervention in a crisis to which zero or one cost clauses were added (soldiers at risk; national or pooled-budget financing; 2 x 3 factorial) and gave their support (0-1).
ReferenceMader, M., Neubert, M., Münchow, F., Hofmann, S. C., Schoen, H., & Gavras, K. (2024). Crumbling in the face of cost? How cost considerations affect public support for European security and defence cooperation. European Union Politics, 25(3), 483-503.
DOI10.1177/14651165241236777
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/CLI4OL

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

Respondents36,452
Rows (one per respondent, task and profile)36,452
Tasks per respondent (most)1
Profiles per task1
Attributes2

Design

Topicforeign policy security
A profile representspolicy
CountryAT, BE, BG, HR, CZ, DK, EE, FI, FR, DE, GB, GR, HU, IE, IT, LV, LT, NL, PL, PT, RO, SK, SI, ES, SE
Language shownunknown
Language of stored levelsen
Randomization restrictionsunknown
Task orderinferred from row order
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:

ratingSupport for EU military intervention in a crisis (paraphrase; question wording not in the deposit) [rating, 0 (strongly oppose (0)) to 1 (strongly support (1))]

Columns

attr_budgetattr_casualtiescov_agecov_countrycov_educationcov_genderidprofileratingtasktrial_question_order

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("mader_2024_eu_military_costs", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("mader_2024_eu_military_costs", source="conj")

How to cite

@article{Mader_2024, title={Crumbling in the face of cost? How cost considerations affect public support for European security and defence cooperation}, volume={25}, ISSN={1741-2757}, url={http://dx.doi.org/10.1177/14651165241236777}, DOI={10.1177/14651165241236777}, number={3}, journal={European Union Politics}, publisher={SAGE Publications}, author={Mader, Matthias and Neubert, Moritz and Münchow, Felix and Hofmann, Stephanie C and Schoen, Harald and Gavras, Konstantin}, year={2024}, month=Mar, pages={483–503} }

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