goldberg_2018_spa_ipip

57,571 responses from 730 respondents to 79 items.

One of 11 tables from the same source; this one is the ipip table. The others are listed under Related tables.

About this table

DescriptionSkills, Possessions and Abilities (ESCS), the IPIP item block. resp 1-5. 730 respondents x 79 items = 57571 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/IOA6EE

Size and shape

Responses57,571
Respondents730
Items79
Response categories5
Responses per respondent78.864
Responses per item728.747
Density0.998
LongitudinalFALSE

Classification

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

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.

Item text

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

InstrumentEugene-Springfield Community Sample, Skills, Possessions, & Abilities (SPA): Perceptions of Personal Qualities
Mean words per item8.835
Mean characters per item49.152
Mean characters per response19.800
Flesch-Kincaid grade level5.230

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.

Respondent uniqueness. 66% of this table’s respondents are alone in their combination of the 6 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("goldberg_2018_spa_ipip")
# Python
pip install irw

import irw
df = irw.fetch("goldberg_2018_spa_ipip")

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 goldberg_2018_spa_ipip, clear

How to cite

@misc{https://doi.org/10.7910/dvn/ioa6ee,
  doi = {10.7910/DVN/IOA6EE},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/IOA6EE},
  author = {Goldberg, Lewis R.},
  keywords = {Social Sciences},
  title = {(27) Skills, Possessions, and Abilities (SPA)},
  publisher = {Harvard Dataverse},
  year = {2018}
}

Version and provenance

IRW versionv674
Redivis datasetitem_response_warehouse_4 v16.0
Redivis dataset DOI10.57761/3rv0-z494
Manifest pin for this IRW versionv16.0
Metadata sourceirw_meta v59.0