11,587 responses from 850 respondents to 14 items.
One of 2 tables from the same source; this one measures Food Consumption Score (FCS). The others are listed under Related tables.
| Description | 14-item Food Consumption Score (days out of 7 each food group was consumed; G1-G14) from the same survey of Ghanaian farming households |
|---|---|
| Reference | Ahmed A, Dompreh E, Gasparatos A (2019) Human wellbeing outcomes of involvement in industrial crop production: Evidence from sugarcane, oil palm and jatropha sites in Ghana. PLoS ONE. |
| DOI | 10.1371/journal.pone.0215433 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0215433.s003 |
| Responses | 11,587 |
|---|---|
| Respondents | 850 |
| Items | 14 |
| Response categories | 8 |
| Responses per respondent | 13.632 |
| Responses per item | 827.643 |
| Density | 0.974 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Targeted/specific |
| construct type | Behavioral |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| construct name | Food Consumption Score (FCS) |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Food Consumption Score (FCS) module, Section D Food Security |
|---|---|
| Mean words per item | 2.286 |
| Mean characters per item | 17.286 |
| Mean characters per response | 2 |
| Flesch-Kincaid grade level | 4.255 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, ahmed_2019_food_consumption.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). | ID |
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("ahmed_2019_food_consumption")
# Python
pip install irw
import irw
df = irw.fetch("ahmed_2019_food_consumption")
@article{Ahmed_2019, title={Human wellbeing outcomes of involvement in industrial crop production: Evidence from sugarcane, oil palm and jatropha sites in Ghana}, volume={14}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0215433}, DOI={10.1371/journal.pone.0215433}, number={4}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Ahmed, Abubakari and Dompreh, Eric and Gasparatos, Alexandros}, editor={Zerriffi, Hisham}, year={2019}, month=Apr, pages={e0215433} }
| IRW version | v549 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v13.0 |
| Redivis dataset DOI | 10.57761/gpg7-sg87 |
| Manifest pin for this IRW version | v13.0 |
| Metadata source | irw_meta v39.0 |