68,160 responses from 142 respondents to 4,588 items.
| Description | Lexical decision task administered to Mturkers |
|---|---|
| Reference | Ratcliff, R., Hendrickson, A.T. Do data from mechanical Turk subjects replicate accuracy, response time, and diffusion modeling results?. Behav Res 53, 2302–2325 (2021). https://doi.org/10.3758/s13428-021-01573-x |
| DOI | 10.3758/s13428-021-01573-x |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/za9y8/ |
| Responses | 68,160 |
|---|---|
| Respondents | 142 |
| Items | 4,588 |
| Response categories | 2 |
| Responses per respondent | 480 |
| Responses per item | 14.856 |
| Density | 0.105 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Internet-based |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Lexical decision task |
blockiditemorderresprt
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("mturkddm_lexical")
# Python
pip install irw
import irw
df = irw.fetch("mturkddm_lexical")
| 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 |