1,344 responses from 32 respondents to 7 items.
| Description | preference tests in humans and animals |
|---|---|
| Reference | Pfefferle, D., Talbot, S. R., Kahnau, P., Cassidy, L. C., Brockhausen, R. R., Jaap, A., ... & Lewejohann, L. (2025). Advancing preference testing in humans and animals. Behavior Research Methods, 57(7), 193. |
| DOI | 10.3758/s13428-025-02668-5 |
| Licence | GPL-3.0 |
| Source data | https://github.com/mytalbot/simsalRbim_data |
| Responses | 1,344 |
|---|---|
| Respondents | 32 |
| Items | 7 |
| Response categories | 2 |
| Responses per respondent | 42 |
| Responses per item | 192 |
| Density | 6 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Constructed Response |
| primary language(s) | eng |
| construct name | preference test |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Preference Test - Wide valence range (seven OASIS images) |
|---|---|
| Mean words per item | 1 |
| Mean characters per item | 2 |
| Mean characters per response | 2 |
| Flesch-Kincaid grade level | -3.400 |
iditemresptrial
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("simsalRbim_Human_LargeValence_2017")
# Python
pip install irw
import irw
df = irw.fetch("simsalRbim_Human_LargeValence_2017")
| 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 |