14,856 rated or chosen profiles from 2,476 respondents, in up to 3 tasks of 2 profiles varying on 6 attributes.
One of 2 tables from the same source; this one is the social table. The others are listed under Related tables.
| Description | US Qualtrics-panel respondents (June-July 2019, n=2,476) chose in 3 tasks between two climate policy packages varying economic programs, social programs, carbon tax design, household energy cost, annual government spending and sponsor (Experiment 1); forced choice, raked weights. |
|---|---|
| Reference | Bergquist, P., Mildenberger, M., & Stokes, L. C. (2020). Combining climate, economic, and social policy builds public support for climate action in the US. Environmental Research Letters, 15(5), 054019. |
| DOI | 10.1088/1748-9326/ab81c1 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/FYQWMS |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,476 |
|---|---|
| Rows (one per respondent, task and profile) | 14,856 |
| Tasks per respondent (most) | 3 |
| Profiles per task | 2 |
| Attributes | 6 |
| Tasks with no profile chosen | 0 |
| Topic | climate energy environment |
|---|---|
| A profile represents | policy |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| choice | Which policy package would you prefer? [choice, forced] |
|---|
attr_carbon_taxattr_economic_programsattr_energy_costsattr_government_spendingattr_social_programsattr_sponsorattrpos_carbon_taxattrpos_economic_programsattrpos_energy_costsattrpos_government_spendingattrpos_social_programsattrpos_sponsorchoicecov_age_groupcov_attention_passcov_duration_seccov_educationcov_gendercov_ideologycov_incomecov_party_idcov_racecov_survey_weightidprofiletasktrial_benefits
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("bergquist_2020_gnd_social", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("bergquist_2020_gnd_social", source="conj")
@article{Bergquist_2020, title={Combining climate, economic, and social policy builds public support for climate action in the US}, volume={15}, ISSN={1748-9326}, url={http://dx.doi.org/10.1088/1748-9326/ab81c1}, DOI={10.1088/1748-9326/ab81c1}, number={5}, journal={Environmental Research Letters}, publisher={IOP Publishing}, author={Bergquist, Parrish and Mildenberger, Matto and Stokes, Leah C}, year={2020}, month=May, pages={054019} }
| 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 |