3,445 responses from 174 respondents to 20 items.
One of 6 tables from the same source; this one measures Self-deceptive enhancement (BIDR). The others are listed under Related tables.
| Description | Balanced Inventory of Desirable Responding, self-deceptive enhancement: 20 items, 1 = not true to 5 = very true. School teachers in 25 schools in Pakistan (PhD thesis data; English questionnaire); experimental vignette condition in cov_condition, school in cluster_id. N=174. |
|---|---|
| Reference | Khan S (2018). Ethical Leadership, Moral Judgment and Moral Motivation [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/4IZYKK |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/4IZYKK |
| Responses | 3,445 |
|---|---|
| Respondents | 174 |
| Items | 20 |
| Response categories | 5 |
| Responses per respondent | 19.799 |
| Responses per item | 172.250 |
| Density | 0.990 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational, Workplace |
| construct type | Personality |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Self-deceptive enhancement (BIDR) |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, khan_2018_ethical_leadership.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 | ||
cluster_id | IRW standard The group a focal unit is nested in — classroom, teacher, school. | SchoolID |
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 |
cov_condition | Covariate | Condition |
cov_education | Covariate | EduLevel |
cov_gender | Covariate | Gender |
cov_level_taught | Covariate | JobStat |
cov_school_category | Covariate | SchoolCGT |
cov_years_job | Covariate | YearsJob |
cov_years_supervisor | Covariate | YearsSupervisor |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("khan_2018_bidr_sde")
# Python
pip install irw
import irw
df = irw.fetch("khan_2018_bidr_sde")
@misc{https://doi.org/10.7910/dvn/4izykk,
doi = {10.7910/DVN/4IZYKK},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/4IZYKK},
author = {Khan, Shazia},
keywords = {Business and Management, FOS: Economics and business, Ethical Leadership},
title = {Ethical Leadership, Moral Judgment and Moral Motivation},
publisher = {Harvard Dataverse},
year = {2019}
}
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v5.11 |
| Redivis dataset DOI | 10.57761/qahq-j855 |
| Manifest pin for this IRW version | v5.11 |
| Metadata source | irw_meta v44.0 |