goldberg_2018_pas_adjectives

157,935 responses from 733 respondents to 216 items.

One of 2 tables from the same source; this one is the adjectives table. The others are listed under Related tables.

About this table

DescriptionPersonal Attribute Survey (ESCS), person-descriptive adjectives, one per item. resp 1-7. 733 respondents x 216 items = 157935 responses.
ReferenceGoldberg, L. R. (2018). Eugene-Springfield Community Sample [Data set]. Harvard Dataverse. https://dataverse.harvard.edu/dataverse/ESCS-Data
LicenceCC0 1.0
Source datahttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/QYKXUE

Size and shape

Responses157,935
Respondents733
Items216
Response categories7
Responses per respondent215.464
Responses per item731.181
Density0.998
LongitudinalFALSE

Classification

age rangeAdult (18+)
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng

Item text

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

InstrumentPersonal Attribute Survey
Mean words per item1
Mean characters per item9
Mean characters per response88.143
Flesch-Kincaid grade level20.957

Codebook

This codebook is reconstructed by the IRW from the IRW data standard. 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).not traced
itemIRW standard Item identifier.not traced
respIRW standard Response value.not traced
Respondent covariates
cov_ageCovariate not traced
cov_educationCovariate not traced
cov_employmentCovariate not traced
cov_ethnicityCovariate not traced
cov_marital_statusCovariate not traced
cov_sexCovariate not traced

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

Get the data

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

Or load it directly in R or Python:

# R (no account needed)
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("goldberg_2018_pas_adjectives")
# Python (needs a free Redivis account)
pip install irw

import irw
df = irw.fetch("goldberg_2018_pas_adjectives")

How to cite

@misc{https://doi.org/10.7910/dvn/qykxue,
  doi = {10.7910/DVN/QYKXUE},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/QYKXUE},
  author = {Goldberg, Lewis R.},
  keywords = {Social Sciences},
  title = {(15) Personal Attribute Survey (PAS)},
  publisher = {Harvard Dataverse},
  year = {2018}
}

Version and provenance

IRW versionv540
Redivis datasetitem_response_warehouse_4 v13.0
Redivis dataset DOI10.57761/w8zx-td92
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v37.0