18,660 responses from 3,110 respondents to 6 items.
| Description | Likert-scale responses to the presence of discrimination, inequality, and justice in society currently |
|---|---|
| Reference | Friedman, Jeffrey, 2018, "Replication Data for: Priorities for Preventive Action: Explaining Americans' Divergent Reactions to 100 Public Risks", https://doi.org/10.7910/DVN/ZSJA25 |
| Licence | Custom |
| Source data | https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZSJA25 |
| Responses | 18,660 |
|---|---|
| Respondents | 3,110 |
| Items | 6 |
| Response categories | 6 |
| Responses per respondent | 6 |
| Responses per item | 3,110 |
| Density | 1 |
| Longitudinal | TRUE |
| age range | Mixed |
|---|---|
| sample | General/non-specific |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Discrimination |
cov_agecov_democratcov_educationcov_enddatecov_gendercov_hispaniccov_incomecov_independentcov_partycov_racecov_republicancov_sdurationcov_startdatecov_statecov_zipiditemresp
Custom licence — check the terms before reuse at the source data.
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("friedman_2018_risks_discrimination")
# Python
pip install irw
import irw
df = irw.fetch("friedman_2018_risks_discrimination")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v19.0 |
| Redivis dataset DOI | 10.57761/qtx5-4m80 |
| Manifest pin for this IRW version | v19.0 |
| Metadata source | irw_meta v23.0 |