letki_2025_donation

21,346 rated or chosen profiles from 21,346 respondents, in up to 1 tasks of 1 profile varying on 3 attributes.

One of 3 tables from the same source; this one is the donation table. The others are listed under Related tables.

About this table

Description21,346 respondents in 14 post-communist countries (PGPE survey, 2013-2014) each saw one version of a vignette about a donation request (who asks, the amount in public-transport tickets, and the cause) and rated how likely they were to make the donation (1 very likely to 4 not likely at all).
ReferenceLetki, N. (2025). Public goods through private eyes. Exploring citizens' attitudes to public goods and the state in Central Eastern Europe [Data set]. Dane Badawcze UW.
LicenceCC BY 4.0
Source datahttps://doi.org/10.58132/sbjiw0

Notes

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

Size and shape

Respondents21,346
Rows (one per respondent, task and profile)21,346
Tasks per respondent (most)1
Profiles per task1
Attributes3

Design

Topicsocial identity interpersonal
A profile representsscenario
CountryBG, HR, CZ, EE, HU, LV, LT, MD, PL, RO, RS, SK, SI, UA
Language shownunknown
Language of stored levelsen
Task orderinferred from row order
Profile positioninferred from row order

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

ratingHow likely is it that you will make THIS DONATION? (master English questionnaire, card B02) [rating, 1 (Very likely) to 4 (Not likely at all)]

Columns

attr_amountattr_purposeattr_requestercov_age_groupcov_birth_yearcov_countrycov_educationcov_survey_weightidprofileratingtask

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 neededBrowse on Redivisexplore and queryCroissant 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("letki_2025_donation", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("letki_2025_donation", source="conj")

How to cite

@misc{https://doi.org/10.58132/sbjiw0,
  doi = {10.58132/SBJIW0},
  url = {https://danebadawcze.uw.edu.pl/citation?persistentId=doi:10.58132/SBJIW0},
  author = {Letki, Natalia},
  title = {Public goods through private eyes. Exploring citizens' attitudes to public goods and the state in Central Eastern Europe},
  publisher = {Dane Badawcze UW},
  year = {2025}
}

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint_2 v1.4
Redivis dataset DOI10.57761/hk97-wv30
Manifest pin for this IRW versionv1.4
Metadata sourceirw_meta v44.0