9,550 rated or chosen profiles from 4,775 respondents, in up to 2 tasks of 1 profile varying on 3 attributes.
One of 2 tables from the same source; this one is the 2020 table. The others are listed under Related tables.
| Description | German online-panel respondents (n = 4,775, April/May 2020) each read a medical-aid and a financial-aid COVID-19 vignette with randomized recipient community (German state/EU/non-EU), control (health system or fiscal discipline) and costs (medical risk or tax increase), and rated support 1-7. |
|---|---|
| Reference | Heermann, M., Koos, S., & Leuffen, D. (2022). Who deserves European solidarity? How recipient characteristics shape public support for international medical and financial aid during COVID-19. British Journal of Political Science. |
| DOI | 10.1017/S0007123422000357 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/RCO69B |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 4,775 |
|---|---|
| Rows (one per respondent, task and profile) | 9,550 |
| Tasks per respondent (most) | 2 |
| Profiles per task | 1 |
| Attributes | 3 |
| Topic | international economy |
|---|---|
| A profile represents | place |
| Country | DE |
| Language shown | de |
| Language of stored levels | en |
| Task order | unknown |
| Profile position | recorded in the deposit |
Outcomes:
| rating | Would you support such an initiative? (medical aid: your state provides ventilators to another German state; financial aid: Germany provides financial assistance to another EU country) (translated) [rating, 1 (not support at all) to 7 (strongly support)] |
|---|
attr_communityattr_controlattr_costscov_age_groupcov_altruismcov_cosmopolitanismcov_eastcov_educationcov_eu_identitycov_gendercov_incomecov_left_rightcov_survey_weightidprofileratingtasktrial_celltrial_vignette
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.
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("heermann_2022_covid_aid_2020", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("heermann_2022_covid_aid_2020", source="conj")
@article{Heermann_2022, title={Who Deserves European Solidarity? How Recipient Characteristics Shaped Public Support for International Medical and Financial Aid during COVID-19}, volume={53}, ISSN={1469-2112}, url={http://dx.doi.org/10.1017/S0007123422000357}, DOI={10.1017/s0007123422000357}, number={2}, journal={British Journal of Political Science}, publisher={Cambridge University Press (CUP)}, author={Heermann, Max and Koos, Sebastian and Leuffen, Dirk}, year={2022}, month=Dec, pages={629–651} }
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint_2 v1.4 |
| Redivis dataset DOI | 10.57761/hk97-wv30 |
| Manifest pin for this IRW version | v1.4 |
| Metadata source | irw_meta v44.0 |