29,514 rated or chosen profiles from 984 respondents, in up to 15 tasks of 2 profiles varying on 6 attributes.

About this table

Description	US MTurk workers (April 2020, n=984) compared 15 pairs of hypothetical job offers varying the state governor's COVID-19 response, location, company size, state partisanship, salary and company culture; they chose the more attractive offer and rated each offer's attractiveness (1-5).
Reference	Nelson, M. J., & Witko, C. (2020). Government reputational effects of COVID-19 public health actions: A job opportunity evaluation conjoint experiment. Journal of Behavioral Public Administration, 3(1).
DOI	10.30636/jbpa.31.174
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/GOWG6K

Notes

Conjoint table (irw_conjoint). choice = which of the two job offers was most attractive / more likely to be accepted (paraphrase), forced choice, no opt-out; rating = attractiveness of each offer, 1 = Not at all attractive to 5 = Very attractive (the authors' recode of the raw Qualtrics codes). Attributes fully randomized (article); level text from the article's example trial and notes, with the two Trump political-climate levels and two location levels not seen displayed. Demographics other than birth year, 7-point party ID and COVID concern dropped (unlabelled); N = 984 (article: about 1,000).

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

Size and shape

Respondents	984
Rows (one per respondent, task and profile)	29,514
Tasks per respondent (most)	15
Profiles per task	2
Attributes	6
Tasks with no profile chosen	0

Design

Topic	labour hiring
A profile represents	product service
Country	US
Language shown	en
Language of stored levels	en
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Select which of the two job offers was most attractive / which one you would be more likely to accept (paraphrase) [choice, forced]
rating	Rate the attractiveness of each job offer on a 5-point scale ranging from 'Very attractive' to 'Not at all attractive' (paraphrase) [rating, 1 (Not at all attractive) to 5 (Very attractive)]

Columns

attr_company_cultureattr_company_sizeattr_local_newsattr_locationattr_political_climateattr_salarychoicecov_birth_yearcov_covid_concerncov_party_id7_codeidprofileratingtask

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("nelson_2020_covid_job_offers", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("nelson_2020_covid_job_offers", source="conj")

How to cite

@article{Nelson_2020, title={Government reputational effects of COVID-19 public health actions: A job opportunity evaluation conjoint experiment}, volume={3}, ISSN={2576-6465}, url={http://dx.doi.org/10.30636/jbpa.31.174}, DOI={10.30636/jbpa.31.174}, number={1}, journal={Journal of Behavioral Public Administration}, publisher={Center for Experimental and Behavioral Public Administration}, author={Nelson, Michael J. and Witko, Christopher}, year={2020}, month=May }

Version and provenance

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