mexico_2023_quality_problems
587,382 responses from 78,896 respondents to 12 items.
About this table
| Description | Worst Problems Identified |
|---|
| Reference | INEGI. Encuesta Nacional de Calidad e Impacto Gubernamental 2023. SNIEG. Información de Interés Nacional |
|---|
| Licence | Permission via Email |
|---|
| Source data | https://www.inegi.org.mx/programas/encig/2023/#microdatos |
|---|
Size and shape
| Responses | 587,382 |
|---|
| Respondents | 78,896 |
|---|
| Items | 12 |
|---|
| Response categories | 2 |
|---|
| Responses per respondent | 7.445 |
|---|
| Responses per item | 48948.500 |
|---|
| Density | 0.620 |
|---|
| Longitudinal | FALSE |
|---|
Classification
| age range | Adult (18+) |
|---|
| sample | General/non-specific |
|---|
| construct type | Opinion/attitude |
|---|
| measurement tool | Survey/questionnaire |
|---|
| item format | Likert Scale/selected response |
|---|
| primary language(s) | spa |
|---|
| construct name | Problem Severity Assessment |
|---|
Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Worst Problems Identified |
|---|
| Mean words per item | 3.417 |
|---|
| Mean characters per item | 23.667 |
|---|
| Mean characters per response | 13.500 |
|---|
| Flesch-Kincaid grade level | 10.782 |
|---|
Columns
cov_agecov_educationcov_hhsizecov_sexiditemresp
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("mexico_2023_quality_problems")
# Python
pip install irw
import irw
df = irw.fetch("mexico_2023_quality_problems")
Version and provenance
| 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 |
|---|