1,035 responses from 345 respondents to 3 items.
One of 3 tables from the same source; this one is the subj_norm table. The others are listed under Related tables.
| Description | 3-item Subjective Norm scale (father/mother/teacher, -2..2 Likert) from the same TPB survey of Lebanese secondary school students |
|---|---|
| Reference | Hayek J, Schneider F, Lahoud N, Tueni M, de Vries H (2022) Authoritative parenting stimulates academic achievement, also partly via self-efficacy and intention towards getting good grades. PLOS ONE 17(3): e0265595. |
| DOI | 10.1371/journal.pone.0265595 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0265595.s001 |
| Responses | 1,035 |
|---|---|
| Respondents | 345 |
| Items | 3 |
| Response categories | 5 |
| Responses per respondent | 3 |
| Responses per item | 345 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| child age (for child-focused studies) | Adolescent (12-18y) |
| sample | Educational |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | ara |
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 has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Social norms towards getting good academic grades (I-Change Model socio-cognitive measures) |
|---|---|
| Mean words per item | 9 |
| Mean characters per item | 48.333 |
| Mean characters per response | 14 |
| Flesch-Kincaid grade level | 6.276 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, hayek_2022_attitude.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.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | ID |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | Age.2 |
cov_gender | Covariate 1 = Male · 2 = Female | Gender |
cov_school_type | Covariate 1 = Public · 2 = Private | Type_sch |
Covariate value labels are the source’s own, as the IRW recorded them. What item codes and any unlabelled values stand for is in the source’s questionnaire, S1_File.pdf, which shows the item wording.
Respondent uniqueness. No respondent in this table is unique on the 2 covariates above: every one of them shares their combination with someone else. The IRW republishes the demographics its sources published and never at finer granularity: see the data standard.
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("hayek_2022_subj_norm")
# Python
pip install irw
import irw
df = irw.fetch("hayek_2022_subj_norm")
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 hayek_2022_subj_norm, clear
@article{Hayek_2022, title={Authoritative parenting stimulates academic achievement, also partly via self-efficacy and intention towards getting good grades}, volume={17}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0265595}, DOI={10.1371/journal.pone.0265595}, number={3}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Hayek, Joyce and Schneider, Francine and Lahoud, Nathalie and Tueni, Maya and de Vries, Hein}, editor={Kumar, Santosh}, year={2022}, month=Mar, pages={e0265595} }
| IRW version | v674 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v15.0 |
| Redivis dataset DOI | 10.57761/6rg4-6f73 |
| Manifest pin for this IRW version | v15.0 |
| Metadata source | irw_meta v59.0 |