45,840 responses from 236 respondents to 81 items.
| Description | Nelson–Denny Vocabulary Test: Assesses vocabulary knowledge as a measure of crystallized intelligence. Includes 80 items with five response alternatives. |
|---|---|
| Reference | Vermeiren, H., Vandendaele, A., & Brysbaert, M. (2023). Validated tests for language research with university students whose native language is English: Tests of vocabulary, general knowledge, author recognition, and reading comprehension. Behavior Research Methods, 55(3), 1036-1068. |
| DOI | 10.3758/s13428-022-01856-x |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/ef3s4/ |
| Responses | 45,840 |
|---|---|
| Respondents | 236 |
| Items | 81 |
| Response categories | 2 |
| Responses per respondent | 194.237 |
| Responses per item | 565.926 |
| Density | 2.398 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Nelson-Denny Vocabulary Test |
cov_agecov_countrycov_educationcov_gendercov_statuscov_studycov_workstatusiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("vermeiren_2022_nd")
# Python
pip install irw
import irw
df = irw.fetch("vermeiren_2022_nd")
| 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 |