32,111 responses from 711 respondents to 70 items.
| Description | Informant ratings of moral character for team members in Chinese engineering teams. |
|---|---|
| Reference | Sun, J., Wu, W., & Goodwin, G. P. (2025). Are moral people happier? Answers from reputation-based measures of moral character. Journal of Personality and Social Psychology, 128(5), 1160–1180. |
| DOI | 10.1037/pspp0000539 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/5e9y3/overview |
| Responses | 32,111 |
|---|---|
| Respondents | 711 |
| Items | 70 |
| Response categories | 9 |
| Responses per respondent | 45.163 |
| Responses per item | 458.729 |
| Density | 0.645 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| sample | Targeted/specific |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Slider/continuous |
| primary language(s) | eng, chi |
| construct name | Informat Moral Character |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Informant ratings of moral character for team members in Chinese engineering teams. |
|---|---|
| Mean words per item | 1 |
| Mean characters per item | 7.300 |
| Mean characters per response | 2.333 |
| Flesch-Kincaid grade level | 11.940 |
cov_locationcov_teamidcov_teamsizeiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("sun_2025_morality_study2_informant-moral-character")
# Python
pip install irw
import irw
df = irw.fetch("sun_2025_morality_study2_informant-moral-character")
| 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 |