1,611 responses from 230 respondents to 18 items.
| Description | Letter number sequencing |
|---|---|
| Reference | Martinez, D. (2024). Scoring story recall for individual differences research: Central details, peripheral details, and automated scoring. Behavior Research Methods, 1-17. |
| DOI | 10.3758/s13428-024-02480-7 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/5qxkh/ |
| Responses | 1,611 |
|---|---|
| Respondents | 230 |
| Items | 18 |
| Response categories | 2 |
| Responses per respondent | 7.004 |
| Responses per item | 89.500 |
| Density | 0.389 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Targeted/specific |
| construct type | Cognitive/educational |
| measurement tool | Observational rating |
| item format | Constructed Response |
| primary language(s) | eng |
| construct name | Individual differences in story recall |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("idcr_martinez_2023_lns")
# Python
pip install irw
import irw
df = irw.fetch("idcr_martinez_2023_lns")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse v53.0 |
| Redivis dataset DOI | 10.57761/4g08-xt41 |
| Manifest pin for this IRW version | v53.0 |
| Metadata source | irw_meta v23.0 |