meng_2017_referent_assignment

1,480 responses from 74 respondents to 5 items.

About this table

Description5 raw explicit/ambiguous-question referent-assignment correctness scores per trial (74 children x 4 trials, wave-coded)
ReferenceMeng X, Murakami T, Hashiya K (2017). Phonological loop affects children's interpretations of explicit but not ambiguous questions: Research on links between working memory and referent assignment. PLOS ONE, 12(10), e0187368. https://doi.org/10.1371/journal.pone.0187368
DOI10.1371/journal.pone.0187368
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0187368.s001

Size and shape

Responses1,480
Respondents74
Items5
Response categories2
Responses per respondent20
Responses per item296
Density4
LongitudinalTRUE

Classification

sampleEducational
measurement toolTest
item formatConstructed Response
primary language(s)chi

Item text

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

InstrumentReference assignment task (Murakami & Hashiya, 2014)
Mean words per item8.200
Mean characters per item49.200
Mean characters per response8
Flesch-Kincaid grade level1.092

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, meng_2017_referent_assignment.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.

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).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
waveIRW standard Longitudinal wave indicator.made in the build script
Respondent covariates
cov_age_monthsCovariate month
cov_cesCovariate CES
cov_lpsCovariate LPS
cov_patternCovariate pattern
cov_sexCovariate sex

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 (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("meng_2017_referent_assignment")
# Python
pip install irw

import irw
df = irw.fetch("meng_2017_referent_assignment")

How to cite

@article{Meng_2017, title={Phonological loop affects children’s interpretations of explicit but not ambiguous questions: Research on links between working memory and referent assignment}, volume={12}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0187368}, DOI={10.1371/journal.pone.0187368}, number={10}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Meng, Xianwei and Murakami, Taro and Hashiya, Kazuhide}, editor={Allen, Philip}, year={2017}, month=Oct, pages={e0187368} }

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse_3 v13.0
Redivis dataset DOI10.57761/gpg7-sg87
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v39.0