20,121 responses from 1,677 respondents to 12 items.
| Description | Twelve-item Raven-type matrices test scored 0/1 against a key derived from the deposited total score, with per-item response time (rt, seconds); N = 1,677 partnered adults in Florence and Oslo (2019); cov_country, cov_sex, cov_age, cov_education, cov_occupation, cov_civil_status, cov_children. |
|---|---|
| Reference | Rapallini, C., Minello, A., Vignoli, D., & Rustichini, A. (2023). Replication Data for: Fluid intelligence and fertility intentions (V1). Harvard Dataverse. https://doi.org/10.7910/DVN/FSRV5D |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/FSRV5D |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Responses | 20,121 |
|---|---|
| Respondents | 1,677 |
| Items | 12 |
| Response categories | 2 |
| Responses per respondent | 11.998 |
| Responses per item | 1676.750 |
| Density | 1.000 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | General/non-specific |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| construct name | Fluid intelligence (12 Raven-type matrices) |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, rapallini_2023_raven.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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
rt | IRW standard Response time. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | Age |
cov_children | Covariate 0 = No children · 1 = One · 2 = Two · 3 = Three or more | children |
cov_civil_status | Covariate 0 = Not married not cohabiting · 1 = Married/civil union · 2 = Cohabitant | civils |
cov_country | Covariate 1 = Italy · 2 = Norway | country |
cov_education | Covariate 1 = Lower Middle school · 2 = High School · 3 = College and post-Grad | Education |
cov_occupation | Covariate 1 = No work · 2 = Temporary · 3 = Permanent | Occupation |
cov_sex | Covariate 0 = Male · 1 = female | sex |
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 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("rapallini_2023_raven")
# Python
pip install irw
import irw
df = irw.fetch("rapallini_2023_raven")
@misc{https://doi.org/10.7910/dvn/fsrv5d,
doi = {10.7910/DVN/FSRV5D},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/FSRV5D},
author = {Rapallini, Chiara and Minello, Alessandra and Vignoli, Daniele and Rustichini, Aldo},
keywords = {Social Sciences, fertility intentions, fluid intelligence},
title = {Replication Data for: Fluid intelligence and fertility intentions},
publisher = {Harvard Dataverse},
year = {2023}
}
| IRW version | v607 |
|---|---|
| Redivis dataset | item_response_warehouse_5 v10.0 |
| Redivis dataset DOI | 10.57761/45xf-md22 |
| Manifest pin for this IRW version | v9.0 |
| Metadata source | irw_meta v47.0 |