4,382 rated or chosen profiles from 709 respondents, in up to 4 tasks of 2 profiles varying on 8 attributes.
One of 2 tables from the same source; this one is the household table. The others are listed under Related tables.
| Description | Adults in five Tunisian governorates (BJKA face-to-face household survey, July 2017; 709 of 1,193 answered at least one task) chose between two hypothetical candidates in up to 4 pairs varying sex, party, job, town, education, age, policy priority and government experience, after a randomized municipal or national-election prompt. |
|---|---|
| Reference | Blackman, A. D., & Jackson, M. (2021). Gender stereotypes, political leadership, and voting behavior in Tunisia. Political Behavior, 43(3), 1037-1066. |
| DOI | 10.1007/s11109-019-09582-5 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/HPMEVO |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 709 |
|---|---|
| Rows (one per respondent, task and profile) | 4,382 |
| Tasks per respondent (most) | 4 |
| Profiles per task | 2 |
| Attributes | 8 |
| Tasks with no profile chosen | 0 |
| Topic | candidate choice |
|---|---|
| A profile represents | person |
| Country | TN |
| Language shown | ar |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| choice | Choice of one of two candidates (paraphrase; wording not in the deposit) [choice, forced] |
|---|
attr_ageattr_educationattr_experienceattr_jobattr_partyattr_policyattr_sexattr_townchoicecov_agecov_educationcov_enumerator_gendercov_gendercov_governoratecov_party_idcov_women_educationcov_women_jobscov_women_leadersidprofiletasktrial_election
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("blackman_2021_tunisia_household", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("blackman_2021_tunisia_household", source="conj")
@article{Blackman_2019, title={Gender Stereotypes, Political Leadership, and Voting Behavior in Tunisia}, volume={43}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-019-09582-5}, DOI={10.1007/s11109-019-09582-5}, number={3}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Blackman, Alexandra Domike and Jackson, Marlette}, year={2019}, month=Nov, pages={1037–1066} }
| 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 |