1,998 responses from 17 respondents to 3 items.
| Description | Discrimination of odor mixture samples |
|---|---|
| Reference | Curtis R Luckett, Robert Pellegrino, Michelle Heatherly, Katherine Alfaro Martinez, Melissa Dein, P John Munafo, Discrimination of Complex Odor Mixtures: A Study Using Wine Aroma Models, Chemical Senses, Volume 46, 2021, bjaa079, https://doi.org/10.1093/chemse/bjaa079 |
| DOI | 10.1093/chemse/bjaa079 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/nwv5a/ |
| Responses | 1,998 |
|---|---|
| Respondents | 17 |
| Items | 3 |
| Response categories | 100 |
| Responses per respondent | 117.529 |
| Responses per item | 666 |
| Density | 39.176 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Targeted/specific |
| construct type | Behavioral, Cognitive/educational |
| measurement tool | Observational rating |
| item format | Mixed |
| primary language(s) | eng |
| construct name | Discrimination of Complex Odor Mixtures: A Study Using Wine Aroma Models |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Aroma rating task, wine aroma model study (Luckett et al. 2021, Chemical Senses) |
|---|---|
| Mean words per item | 6.085 |
| Mean characters per item | 31.415 |
| Mean characters per response | 2 |
| Flesch-Kincaid grade level | 4.401 |
iditemraterresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("wine_luckett2021")
# Python
pip install irw
import irw
df = irw.fetch("wine_luckett2021")
| 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 |