952 rated or chosen profiles from 952 respondents, in up to 1 tasks of 1 profile varying on 5 attributes.
| Description | Factorial vignette on legislators' credit claiming: 952 US online respondents (MTurk, June 2013) each read one press release varying the legislator's party, whether credit was claimed alone or with a Democrat/Republican, the stage (requested, secured, will request), the amount ($20 million or $50 thousand) and the project type; outcomes are 1-5 approval and a 0-100 thermometer rating of the legislator. |
|---|---|
| Reference | Grimmer, J., Messing, S., & Westwood, S. J. (2017). Estimating heterogeneous treatment effects and the effects of heterogeneous treatments with ensemble methods. Political Analysis, 25(4), 413-434. |
| DOI | 10.1017/pan.2017.15 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/BQMLQW |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 952 |
|---|---|
| Rows (one per respondent, task and profile) | 952 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 5 |
| Topic | corruption accountability, political communication |
|---|---|
| A profile represents | message |
| Country | US |
| Language shown | en |
| 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 | Do you approve or disapprove of the legislator? (paraphrase) [rating, 1 (unknown) to 5 (unknown)] |
|---|---|
| rating_therm | Feeling thermometer toward the legislator, 0-100 (paraphrase) [rating, 0 (unknown) to 100 (unknown)] |
attr_along_withattr_moneyattr_partyattr_stageattr_typecov_byear_codecov_duration_seccov_educ_codecov_gender_codecov_ideo3_codecov_inc_codecov_pid3_codecov_pidcloser_codecov_race_codecov_voted_codeidprofileratingrating_thermtask
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("grimmer_2017_credit_claiming", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("grimmer_2017_credit_claiming", source="conj")
@article{Grimmer_2017, title={Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods}, volume={25}, ISSN={1476-4989}, url={http://dx.doi.org/10.1017/pan.2017.15}, DOI={10.1017/pan.2017.15}, number={4}, journal={Political Analysis}, publisher={Cambridge University Press (CUP)}, author={Grimmer, Justin and Messing, Solomon and Westwood, Sean J.}, year={2017}, month=Sept, pages={413–434} }
| 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 |