6,552 responses from 234 respondents to 28 items.
| Description | COVID-19 impact questionnaire for Chinese SMEs (28 items); N=234; 1-7 Likert; covers financial performance, operations, costs, and government relief |
|---|---|
| Reference | Ma, Z., Liu, Y., & Gao, Y. (2022). Replication Data for: Valid questionnaire for small and medium-sized enterprises [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/0ADT0D |
| DOI | 10.1371/journal.pone.0257036 |
| Licence | CC0 1.0 |
| Source data | https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/0ADT0D |
| Responses | 6,552 |
|---|---|
| Respondents | 234 |
| Items | 28 |
| Response categories | 7 |
| Responses per respondent | 28 |
| Responses per item | 234 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Questionnaire of impact of COVID-19 on small and medium-sized enterprises |
|---|---|
| Mean words per item | 15.429 |
| Mean characters per item | 109.607 |
| Mean characters per response | 2.714 |
| Flesch-Kincaid grade level | 13.529 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("ma2021_sme_covid")
# Python
pip install irw
import irw
df = irw.fetch("ma2021_sme_covid")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v19.0 |
| Redivis dataset DOI | 10.57761/qtx5-4m80 |
| Manifest pin for this IRW version | v19.0 |
| Metadata source | irw_meta v23.0 |