About this table

Description	Support-network composition by relationship type, elderly Slovenians, 7 items, N=558
Reference	Cugmas, M., et al. (2021). The social support networks of elderly people in Slovenia during the Covid-19 pandemic. PLOS ONE.
DOI	10.1371/journal.pone.0247993
Licence	CC BY 4.0
Source data	https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0247993

Size and shape

Responses	3,906
Respondents	558
Items	7
Response categories	15
Responses per respondent	7
Responses per item	558
Density	1
Longitudinal	FALSE

Classification

sample	Internet-based
measurement tool	Survey/questionnaire
item format	Mixed
primary language(s)	slv

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

Instrument	Egocentric social support network name generators with relationship-type name interpreter (Questionnaire on Social Support Networks during the Coronavirus Pandemic)
Mean words per item	1.188
Mean characters per item	8.125
Mean characters per response	2
Flesch-Kincaid grade level	36.097

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, cugmas_2021_elderly_social_support.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
Respondent covariates
`cov_age_rank`	Covariate	`starank`
`cov_education`	Covariate	`edu`
`cov_gender`	Covariate	`gndr`
`cov_marital_status`	Covariate	`martial`
`cov_region`	Covariate	`region`

What item codes and covariate values stand for is in the source’s questionnaire, S1_Questionnaire.pdf, S2_Questionnaire.pdf, which show the item wording.

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant metadataHugging Face, Kaggle, OpenML

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("cugmas_2021_elderly_social_support")

# Python
pip install irw

import irw
df = irw.fetch("cugmas_2021_elderly_social_support")

How to cite

@article{Cugmas_2021, title={The social support networks of elderly people in Slovenia during the Covid-19 pandemic}, volume={16}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0247993}, DOI={10.1371/journal.pone.0247993}, number={3}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Cugmas, Marjan and Ferligoj, Anuška and Kogovšek, Tina and Batagelj, Zenel}, editor={Pan, Xi}, year={2021}, month=Mar, pages={e0247993} }

Version and provenance

IRW version	v566
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 v43.0