muller_2016_dog_inhibition

115 responses from 41 respondents to 3 items.

About this table

DescriptionInhibitory-control (cylinder) task, pet dogs, 3 trials, 0-2 ordinal, N=41
ReferenceMüller, C. A., Riemer, S., Virányi, Z., Huber, L., & Range, F. (2016). Inhibitory control, but not prolonged object-related experience appears to affect physical problem-solving performance of pet dogs. PLOS ONE.
DOI10.1371/journal.pone.0147753
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147753

Size and shape

Responses115
Respondents41
Items3
Response categories3
Responses per respondent2.805
Responses per item38.333
Density0.935
LongitudinalFALSE

Classification

age rangeNot applicable (non-person)
sampleAnimal
measurement toolObservational rating

Item text

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

InstrumentInhibitory control tasks (wait-for-treat, middle cup, leash), Muller et al. 2016
Mean words per item55
Mean characters per item288
Mean characters per response83.111
Flesch-Kincaid grade level9.189

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, muller_2016_dog_inhibition.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).ID
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_sexCovariate Sex
cov_treatmentCovariate Treatment

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("muller_2016_dog_inhibition")
# Python
pip install irw

import irw
df = irw.fetch("muller_2016_dog_inhibition")

How to cite

@article{M_ller_2016, title={Inhibitory Control, but Not Prolonged Object-Related Experience Appears to Affect Physical Problem-Solving Performance of Pet Dogs}, volume={11}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0147753}, DOI={10.1371/journal.pone.0147753}, number={2}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Müller, Corsin A. and Riemer, Stefanie and Virányi, Zsófia and Huber, Ludwig and Range, Friederike}, editor={Addessi, Elsa}, year={2016}, month=Feb, pages={e0147753} }

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_3 v14.0
Redivis dataset DOI10.57761/rkkt-p907
Manifest pin for this IRW versionv14.0
Metadata sourceirw_meta v44.0