ganbat_2022_pollution_leave_type

6,645 responses from 1,329 respondents to 5 items.

One of 3 tables from the same source; this one is the leave_type table. The others are listed under Related tables.

About this table

Description5-item binary (0/1) checklist of leave type used when absent for illness, from the same survey of Ulaanbaatar workers
ReferenceGanbat A, Erdenebileg T, Batbold A, et al. (2022) Integrating quantitative and qualitative approaches to assess wintertime illness-related absenteeism and its direct and indirect costs among the private sector in Ulaanbaatar. PLoS ONE.
DOI10.1371/journal.pone.0263220
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0263220.s004&type=supplementary

Size and shape

Responses6,645
Respondents1,329
Items5
Response categories2
Responses per respondent5
Responses per item1,329
Density1
LongitudinalFALSE

Classification

sampleWorkplace
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)mon

Item text

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

InstrumentWintertime illness-related absenteeism survey (Ulaanbaatar private sector), Q7: type of temporary leave
Mean words per item2.400
Mean characters per item14.800
Mean characters per response2
Flesch-Kincaid grade level2.297

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, ganbat_2022_air_pollution.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.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).ID
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script

What item codes and covariate values stand for is in the source’s codebook, codebook (sheet in S4_File.xlsx).

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant 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("ganbat_2022_pollution_leave_type")
# Python
pip install irw

import irw
df = irw.fetch("ganbat_2022_pollution_leave_type")

How to cite

@article{Ganbat_2022, title={Integrating quantitative and qualitative approaches to assess wintertime illness-related absenteeism and its direct and indirect costs among the private sector in Ulaanbaatar}, volume={17}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0263220}, DOI={10.1371/journal.pone.0263220}, number={2}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Ganbat, Mandukhai and Erdenebileg, Nasantogtokh and Batbold, Chuluunbileg and Nergui, Saruultuya and Anderson, Ron and Wigfall, Clarence and Amarsanaa, Narantsetseg and Heikens, Alex and Sarantuya, Moiltmaa and Warburton, David}, editor={Jiménez, Natalia}, year={2022}, month=Feb, pages={e0263220} }

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse_4 v13.0
Redivis dataset DOI10.57761/w8zx-td92
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v39.0