14,804 rated or chosen profiles from 3,701 respondents, in up to 1 tasks of 4 profiles varying on 4 attributes.
| Description | 3,701 US adults (national, Black and Latino samples) each rated four hypothetical neighbours differing in name, age, occupation and community involvement (charity, rallies, voting, or a potluck control) on 1-7 likability and respectability. |
|---|---|
| Reference | Anoll, A. P. (2018). What makes a good neighbor? Race, place, and norms of political participation. American Political Science Review, 112(3), 494-508. |
| DOI | 10.1017/S0003055418000175 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/SJI4IA |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 3,701 |
|---|---|
| Rows (one per respondent, task and profile) | 14,804 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 4 |
| Attributes | 4 |
| Topic | social identity interpersonal |
|---|---|
| A profile represents | person |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | yes (stated by the source): Each respondent sees each name, age, occupation and the three community actions exactly once across the four profiles (drawn without repetition); the potluck control is always profile 4, other values in random order |
| Task order | inferred from row order |
| Profile position | recorded in the deposit |
Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead. Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| rating_like | Likability rating of the neighbour on a 1-7 scale (wording not in the deposit; the authors' code calls it 'Likability') (paraphrase) [rating, 1 (unknown) to 7 (unknown)] |
|---|---|
| rating_respect | Respectability rating of the neighbour on a 1-7 scale (wording not in the deposit; the authors' code calls it 'Respectability score') (paraphrase) [rating, 1 (unknown) to 7 (unknown)] |
attr_ageattr_community_involvementattr_nameattr_occupationcov_birth_yearcov_education_codecov_gendercov_income_codecov_party_idcov_racecov_samplecov_stateidprofilerating_likerating_respecttask
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("anoll_2018_good_neighbor", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("anoll_2018_good_neighbor", source="conj")
@article{ANOLL_2018, title={What Makes a Good Neighbor? Race, Place, and Norms of Political Participation}, volume={112}, ISSN={1537-5943}, url={http://dx.doi.org/10.1017/S0003055418000175}, DOI={10.1017/s0003055418000175}, number={3}, journal={American Political Science Review}, publisher={Cambridge University Press (CUP)}, author={ANOLL, ALLISON P.}, year={2018}, month=May, pages={494–508} }
| 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 |