1,613 rated or chosen profiles from 1,613 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.
| Description | 1,613 Danish adults (YouGov panel, 2021) read one vignette about helping a relative apply for a nursing-home place, in which the municipality's decision (rejected or approved) and the caseworker's warmth (low or high) were randomized. Outcomes: trust in the caseworker, trust in the municipality (0-1) and inclination to complain (1-7). |
|---|---|
| Reference | Hansen, F. G. (2023). Can warm behavior mitigate the negative effect of unfavorable governmental decisions on citizens' trust? Journal of Experimental Political Science, 10(1), 62-75. |
| DOI | 10.1017/xps.2021.23 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/dvn/kamsqk |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,613 |
|---|---|
| Rows (one per respondent, task and profile) | 1,613 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 2 |
| Topic | public administration |
|---|---|
| A profile represents | scenario |
| Country | DK |
| Language shown | da |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | inferred from row order |
| 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:
| rating_inclined_to_complain | Hvor tilbøjelig er du til at klage over afgørelsen? (How inclined are you to complain about the decision? 1 Meget tilbøjelig ... 7 Meget utilbøjelig; 88 Ved ikke kept as 88) (translated) [rating, 1 (Very inclined to complain) to 7 (Very disinclined to complain (88 = don't know))] |
|---|---|
| rating_trust_caseworker | How much do you personally trust the caseworker to make the right decisions? (0-10 scale recoded by the author to 0-1; Danish wording not in the deposit) [rating, 0 (No trust at all) to 1 (Completely trust)] |
| rating_trust_municipality | How much do you personally trust the municipality to make the right decisions? (0-10 scale recoded by the author to 0-1; Danish wording not in the deposit) [rating, 0 (No trust at all) to 1 (Completely trust)] |
attr_caseworker_warmthattr_decisioncov_age_groupcov_educationcov_elderly_care_usercov_gendercov_ideology_lridprofilerating_inclined_to_complainrating_trust_caseworkerrating_trust_municipalitytask
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("hansen_2023_warmth", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("hansen_2023_warmth", source="conj")
@article{Hansen_2021, title={Can Warm Behavior Mitigate the Negative Effect of Unfavorable Governmental Decisions on Citizens’ Trust?}, volume={10}, ISSN={2052-2649}, url={http://dx.doi.org/10.1017/xps.2021.23}, DOI={10.1017/xps.2021.23}, number={1}, journal={Journal of Experimental Political Science}, publisher={Cambridge University Press (CUP)}, author={Hansen, Frederik Godt}, year={2021}, month=Aug, pages={62–75} }
| 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 |