1,656 responses from 92 respondents to 18 items.
One of 3 tables from the same source; this one measures Mental Imagery. The others are listed under Related tables.
| Description | Spontaneous Use of Imagery Scale |
|---|---|
| Reference | Suggate, S.P. Beyond self-report: Measuring visual, auditory, and tactile mental imagery using a mental comparison task. Behav Res 56, 8658–8676 (2024). https://doi.org/10.3758/s13428-024-02496-z |
| DOI | 10.3758/s13428-024-02496-z |
| Licence | MIT |
| Source data | https://osf.io/vf27z/?view_only=43c4db49648f428c914ebdcc4e191f27 |
| Responses | 1,656 |
|---|---|
| Respondents | 92 |
| Items | 18 |
| Response categories | 5 |
| Responses per respondent | 18 |
| Responses per item | 92 |
| Density | 1 |
| 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, ger |
| construct name | Mental Imagery |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, DMCT_Addis_2020.r. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | Participant_Code |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("DMCT_Addis_2020_SUIS")
# Python
pip install irw
import irw
df = irw.fetch("DMCT_Addis_2020_SUIS")
@article{Suggate_2024, title={Beyond self-report: Measuring visual, auditory, and tactile mental imagery using a mental comparison task}, volume={56}, ISSN={1554-3528}, url={http://dx.doi.org/10.3758/s13428-024-02496-z}, DOI={10.3758/s13428-024-02496-z}, number={8}, journal={Behavior Research Methods}, publisher={Springer Science and Business Media LLC}, author={Suggate, Sebastian Paul}, year={2024}, month=sep, pages={8658–8676} }
| IRW version | v549 |
|---|---|
| Redivis dataset | item_response_warehouse v70.0 |
| Redivis dataset DOI | 10.57761/4qxs-pq87 |
| Manifest pin for this IRW version | v70.0 |
| Metadata source | irw_meta v39.0 |