38,052 rated or chosen profiles from 3,171 respondents, in up to 6 tasks of 2 profiles varying on 16 attributes.

About this table

Description	Candidate conjoint on anti-Muslim bias: 3,171 Norwegian adults (Verian panel; 629 first-stage baseline respondents plus 2,542 second-stage respondents randomized to five information arms) each chose between two candidates varying gender, age, occupation, family, experience and religion, plus party, policy or personal attributes by arm, in 6 tasks; forced choice.
Reference	Finseraas, H., & Heim, R. (2026). What drives voter bias against Muslim politicians? An experimental examination. Political Behavior.
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/A1OKBZ

Notes

Conjoint table (irw_conjoint). Outcome: forced choice between two candidates (question wording not deposited; the authors describe willingness to vote for them), no opt-out. Pools the first-stage baseline sample (trial_stage 1) with the second-stage sample randomized to five arms that add party, general-policy, minority-rights or personal attributes (trial_arm; attributes not shown are (not shown)). Task 6 repeats task 1 with profiles swapped. Levels are the deposit's English labels (display presumably Norwegian).

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Design

Topic	candidate choice
A profile represents	person
Country	NO
Language shown	unknown
Language of stored levels	en
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Choice between two candidates (paraphrase) [choice, forced]

Columns

attr_ageattr_citiesattr_discriminationattr_euattr_experienceattr_familysitattr_genderattr_immigrationattr_networkattr_occupationattr_partyattr_persvotesattr_prideattr_religionattr_socialmediaattr_ukrainechoicecov_agecov_gendercov_high_educationcov_left_rightcov_paid_workidprofiletasktrial_armtrial_repeat_oftrial_stage

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.

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant metadataHugging Face, Kaggle, OpenML

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("finseraas_2026_muslim_candidates", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("finseraas_2026_muslim_candidates", source="conj")

How to cite

@misc{https://doi.org/10.7910/dvn/a1okbz,
  doi = {10.7910/DVN/A1OKBZ},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/A1OKBZ},
  author = {Finseraas, Henning and Heim, Rino},
  keywords = {Social Sciences},
  title = {Replication Data for: What Drives Voter Bias Against Muslim Politicians? An Experimental Examination},
  publisher = {Harvard Dataverse},
  year = {2026}
}

Respondents	3,171
Rows (one per respondent, task and profile)	38,052
Tasks per respondent (most)	6
Profiles per task	2
Attributes	16
Tasks with no profile chosen	0

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

finseraas_2026_muslim_candidates