Item Response Warehouse / Tables / ganbat_2022_pollution_symptomsganbat_2022_pollution_symptoms
10,631 responses from 1,329 respondents to 8 items.
About this table
Description 8-item binary (0/1) checklist of symptoms experienced during high air-pollution periods, from a survey of private-sector workers in Ulaanbaatar Reference Ganbat 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. DOI 10.1371/journal.pone.0263220 Licence CC BY 4.0 Source data https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0263220.s004&type=supplementary
Size and shape
Responses 10,631 Respondents 1,329 Items 8 Response categories 2 Responses per respondent 7.999 Responses per item 1328.875 Density 1.000 Longitudinal FALSE
Classification
sample Workplace measurement tool Survey/questionnaire item format Likert 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.
Instrument Ulaanbaatar wintertime absenteeism survey: common symptoms related to air pollution (Q1) Mean words per item 4 Mean characters per item 26.500 Mean characters per response 2 Flesch-Kincaid grade level 4.776
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("ganbat_2022_pollution_symptoms")
# Python
pip install irw
import irw
df = irw.fetch("ganbat_2022_pollution_symptoms")
Version and provenance
IRW version v393 Redivis dataset item_response_warehouse_4 v7.0 Redivis dataset DOI 10.57761/cpj5-vm97 Manifest pin for this IRW version v7.0 Metadata source irw_meta v23.0
Part of the Item Response Warehouse , IRW v393. This page describes the table as released in item_response_warehouse_4 v7.0.