59,109 rated or chosen profiles from 2,076 respondents, in up to 10 tasks of 3 profiles varying on 6 attributes.
| Description | US adults (Lucid, December 2022, n=2,076) chose among three hypothetical US vacation destinations (temperature, attractions, travel time, 2020 state election result, recent state news incl. democratic backsliding laws, community type) and rated interest in each; 10 tasks, with a 'none' option. |
|---|---|
| Reference | Miller, D. R., & Smith, S. D. (2024). (Small D-democratic) vacation, all I ever wanted? The effect of democratic backsliding on leisure travel in the American states. Journal of Experimental Political Science, 12, 99-109. |
| DOI | 10.1017/xps.2023.40 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/KA7DLE |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,076 |
|---|---|
| Rows (one per respondent, task and profile) | 59,109 |
| Tasks per respondent (most) | 10 |
| Profiles per task | 3 |
| Attributes | 6 |
| Tasks with no profile chosen | 3,121 |
| Topic | consumer products, democracy institutions |
|---|---|
| A profile represents | place |
| 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 | At which of these destinations are you most interested in vacationing? [choice, opt-out allowed] |
|---|---|
| rating | How interested are you in vacationing at each destination? [rating, 1 (Not at all interested) to 5 (Extremely interested)] |
attr_attractionsattr_communityattr_election_2020attr_recent_newsattr_temperatureattr_travel_timeattrpos_attractionsattrpos_communityattrpos_election_2020attrpos_recent_newsattrpos_temperatureattrpos_travel_timechoicecov_agecov_attention_pass_1cov_attention_pass_2cov_educationcov_gendercov_ideologycov_incomecov_party_idcov_regionidprofileratingtask
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("miller_2024_backsliding_travel", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("miller_2024_backsliding_travel", source="conj")
@article{Miller_2024, title={(Small D-democratic) vacation, all I ever wanted? The effect of democratic backsliding on leisure travel in the American states}, volume={12}, ISSN={2052-2649}, url={http://dx.doi.org/10.1017/xps.2023.40}, DOI={10.1017/xps.2023.40}, number={1}, journal={Journal of Experimental Political Science}, publisher={Cambridge University Press (CUP)}, author={Miller, David R. and Smith, Serena D.}, year={2024}, month=Apr, pages={99–109} }
| 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 |