hamzawi_2025_party_valence

About this table

Notes

• Conjoint table (irw_conjoint). Outcome: forced choice of which of two hypothetical parties' candidate (district vote, trial_context (S/M)MD) or party (PR vote) is preferable; skipping was allowed and the 524 skipped tasks (2.8%) are omitted, so 1,834 of 1,866 respondents remain. Tasks 1-5 are always the district block although block order was randomized for half the sample (not recorded), so task is not the display order across blocks. Levels are the authors' English labels; randomization was restricted to realistic combinations (e.g. MPs vs ministers, committee chairs, bills), so level shares are unequal. Attribute order was randomized per respondent and is kept as attrpos_*.

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

Size and shape

Design

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.

Outcomes:

Columns

attr_bills_introducedattr_committee_chairsattr_districts_with_candidatesattr_leader_personalityattr_leader_tenureattr_ministersattr_mpsattr_mps_reelectedattr_policy_constitutionattr_policy_consumption_taxattr_policy_dual_surnameattr_promises_achievedattr_scandalsattr_years_since_formationattrpos_bills_introducedattrpos_committee_chairsattrpos_districts_with_candidatesattrpos_leader_personalityattrpos_leader_tenureattrpos_ministersattrpos_mpsattrpos_mps_reelectedattrpos_policy_constitutionattrpos_policy_consumption_taxattrpos_policy_dual_surnameattrpos_promises_achievedattrpos_scandalsattrpos_years_since_formationchoicecov_constref_defendcov_constref_excl_art9cov_constref_incl_art9cov_dual_surnamecov_party_idcov_tax_5pctcov_tax_8pctcov_tax_abolishcov_tax_status_quocov_therm_cdpcov_therm_dpfpcov_therm_ishincov_therm_jcpcov_therm_komeitocov_therm_ldpidprofiletasktrial_context

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

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("hamzawi_2025_party_valence", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("hamzawi_2025_party_valence", source="conj")

How to cite

@article{Hamzawi_2025, title={What brings you to the party? Voter preferences on parties through policy and valence dynamics}, volume={32}, ISSN={1460-3683}, url={http://dx.doi.org/10.1177/13540688251339631}, DOI={10.1177/13540688251339631}, number={4}, journal={Party Politics}, publisher={SAGE Publications}, author={Hamzawi, Jordan and Kato, Gento and Endo, Masahisa}, year={2025}, month=May, pages={486–499} }

Version and provenance