56,160 responses from 597 respondents to 80 items.
| Description | EGEFACE: A new face memory test with static and dynamic images |
|---|---|
| Reference | Amado, S., Karataş, M. C., Yuvruk, E., & Kapucu, A. (2024, November 1). EGEFACE: A New Face Memory Test with Static and Dynamic Images. Retrieved from osf.io/gjwk8 |
| DOI | 10.3758/s13428-024-02592-0 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/gjwk8/overview |
| Responses | 56,160 |
|---|---|
| Respondents | 597 |
| Items | 80 |
| Response categories | 6 |
| Responses per respondent | 94.070 |
| Responses per item | 702 |
| Density | 1.176 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | General/non-specific |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Face Memory |
cov_agecov_educationcov_egeface_groupcov_gendercov_handednesscov_p_groupcov_phaseiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("face_memory_amado_2024")
# Python
pip install irw
import irw
df = irw.fetch("face_memory_amado_2024")
| 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 |