2,330 responses from 233 respondents to 10 items.
One of 3 tables from the same source; this one measures Cross-sectional T-MoCA raw subscale scores for 233 Tamil-speaking older adults at one timepoint.. The others are listed under Related tables.
| Description | Cross-sectional T-MoCA raw subscale scores for 233 Tamil-speaking older adults at one timepoint. |
|---|---|
| Reference | Karim, Mani A., and J Venkatachalam. “Construct Validity and Psychometric Properties of the Tamil (india) Version of T-moca.” OSF, 27 Oct. 2022. Web. |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/f7nkg/overview |
| Responses | 2,330 |
|---|---|
| Respondents | 233 |
| Items | 10 |
| Response categories | 2 |
| Responses per respondent | 10 |
| Responses per item | 233 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Elderly (minimum age >50) |
|---|---|
| sample | Targeted/specific |
| construct type | Cognitive/educational |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | tam |
| construct name | Cross-sectional T-MoCA raw subscale scores for 233 Tamil-speaking older adults at one timepoint. |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, Karim2022_tmoca.py. 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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_group_0 | Covariate | made in the build script |
cov_group_code | Covariate | 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("Karim2022_tmoca_mci")
# Python
pip install irw
import irw
df = irw.fetch("Karim2022_tmoca_mci")
@article{https://doi.org/10.17605/osf.io/f7nkg,
doi = {10.17605/OSF.IO/F7NKG},
url = {https://osf.io/f7nkg/},
author = {Venkatachalam, J and Karim, Mani Abdul},
title = {Construct Validity and Psychometric Properties of the Tamil (India) Version of T-MoCA},
publisher = {OSF},
year = {2021}
}
| IRW version | v549 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v33.0 |
| Redivis dataset DOI | 10.57761/6m04-m698 |
| Manifest pin for this IRW version | v33.0 |
| Metadata source | irw_meta v39.0 |