hoorani_2022_sp

2,140 responses from 535 respondents to 4 items.

One of 5 tables from the same source; this one is the sp table. The others are listed under Related tables.

About this table

Description4-item agreement scale (SP, includes a 'more or less' middle option), Young Lives India adolescent cohort panel, wave 2 only
ReferenceHoorani BH, Krishnakumar J, Anand P (2022). Adolescent's time use and skills development: Do cognitive and non-cognitive skills differ?. PLOS ONE, 17(7), e0271374. https://doi.org/10.1371/journal.pone.0271374
DOI10.1371/journal.pone.0271374
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0271374.s016

Size and shape

Responses2,140
Respondents535
Items4
Response categories5
Responses per respondent4
Responses per item535
Density1
LongitudinalTRUE

Classification

sampleProgram-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)tel

These are classifications the IRW records, not the study’s own words. Some were annotated by hand and some written by an automated tagger whose output is published only where it clears a measured accuracy bar; which values came from which is not recorded per table. Coverage and accuracy per column, and what is held back, are on Tag quality.

This table is in 1 collection. Each membership records how it was decided:

Membership is the IRW’s judgment and is worth checking before you use a collection as a sample. A hand-curated list is a snapshot: it is not re-checked when tables are added, so a table that would qualify may be missing. See Collections.

Item text

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

InstrumentYoung Lives Older Cohort Child Questionnaire (India), Round 3 - self-esteem pride items
Mean words per item8.500
Mean characters per item42.500
Mean characters per response11.200
Flesch-Kincaid grade level3.653

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, hoorani_2022_young_lives_battery.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).CHILDID
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
waveIRW standard Longitudinal wave indicator.made in the build script
Respondent covariates
cov_household_sizeCovariate hhsize
cov_maleCovariate male

What item codes and covariate values stand for is in the codebook released with the source data.

Respondent uniqueness. 1% of this table’s respondents are alone in their combination of the 2 covariates above — no one else in the table shares it. That is a necessary condition for re-identification and not re-identification itself, and on a sample this size it is largely arithmetic. The IRW republishes the demographics its sources published and never at finer granularity: see the data standard.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R (no account needed with irw 1.4.0 or later) or Python (needs a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("irw")
library(irw)
df <- irw_fetch("hoorani_2022_sp")
# Python
pip install irw

import irw
df = irw.fetch("hoorani_2022_sp")

Or in Stata, which reads the same no-account CSV as the button above:

* Stata
net install irw, from("https://raw.githubusercontent.com/itemresponsewarehouse/Stata-pkg/main/")

irw_fetch hoorani_2022_sp, clear

How to cite

@article{Hoorani_2022, title={Adolescent’s time use and skills development: Do cognitive and non-cognitive skills differ?}, volume={17}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0271374}, DOI={10.1371/journal.pone.0271374}, number={7}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Hoorani, Bareerah Hafeez and Krishnakumar, Jaya and Anand, Paul}, editor={Asadullah, M Niaz}, year={2022}, month=July, pages={e0271374} }

Version and provenance

IRW versionv674
Redivis datasetitem_response_warehouse_3 v15.0
Redivis dataset DOI10.57761/6rg4-6f73
Manifest pin for this IRW versionv15.0
Metadata sourceirw_meta v59.0