About this table

Description	Skills, Possessions and Abilities (ESCS), medical-history items. resp 1-4. 730 respondents x 28 items = 20304 responses.
Reference	Goldberg, L. R. (2018). Eugene-Springfield Community Sample [Data set]. Harvard Dataverse. https://dataverse.harvard.edu/dataverse/ESCS-Data
Licence	CC0 1.0
Source data	https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/IOA6EE

Size and shape

Responses	20,304
Respondents	730
Items	28
Response categories	4
Responses per respondent	27.814
Responses per item	725.143
Density	0.993
Longitudinal	FALSE

Classification

age range	Adult (18+)
measurement tool	Survey/questionnaire
item format	Likert 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.

Instrument	Eugene-Springfield Community Sample, Skills, Possessions, & Abilities (SPA): Your Medical History
Mean words per item	2.107
Mean characters per item	17.143
Mean characters per response	19.500
Flesch-Kincaid grade level	13.902

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.

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).	not traced
`item`	IRW standard Item identifier.	not traced
`resp`	IRW standard Response value.	not traced
Respondent covariates
`cov_age`	Covariate	not traced
`cov_education`	Covariate	not traced
`cov_employment`	Covariate	not traced
`cov_ethnicity`	Covariate	not traced
`cov_marital_status`	Covariate	not traced
`cov_sex`	Covariate	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 needed Browse on Redivisexplore and query Croissant 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_medical_history")

# Python
pip install irw

import irw
df = irw.fetch("goldberg_2018_spa_medical_history")

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_medical_history, 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 version	v674
Redivis dataset	item_response_warehouse_4 v16.0
Redivis dataset DOI	10.57761/3rv0-z494
Manifest pin for this IRW version	v16.0
Metadata source	irw_meta v59.0

goldberg_2018_spa_medical_history