hicks_2020_bioveda

12,320 responses from 770 respondents to 16 items.

About this table

DescriptionBioVEDA assessment (Biological Variation In Experimental Design And Analysis); 16 binary items; N=770
ReferenceHicks J., Dewey J., Brandvain Y., Schuchardt A. (2020). Development of the Biological Variation In Experimental Design And Analysis (BioVEDA) assessment. PLOS ONE. https://doi.org/10.1371/journal.pone.0236098
DOI10.1371/journal.pone.0236098
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0236098.s003

Size and shape

Responses12,320
Respondents770
Items16
Response categories2
Responses per respondent16
Responses per item770
Density1
LongitudinalFALSE

Classification

sampleEducational
measurement toolTest
item formatLikert Scale/selected response
primary language(s)eng

Item text

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

InstrumentBiological Variation In Experimental Design And Analysis (BioVEDA) assessment
Mean words per item62.688
Mean characters per item361.500
Mean characters per response8
Flesch-Kincaid grade level7.977

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, hicks_2020_bioveda.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).Study_ID
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_roleCovariate Role

What item codes and covariate values stand for is in the source’s codebook, Variables (sheet in S3_File.xlsx).

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("hicks_2020_bioveda")
# Python
pip install irw

import irw
df = irw.fetch("hicks_2020_bioveda")

How to cite

@article{Hicks_2020, title={Development of the Biological Variation In Experimental Design And Analysis (BioVEDA) assessment}, volume={15}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0236098}, DOI={10.1371/journal.pone.0236098}, number={7}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Hicks, Jenna and Dewey, Jessica and Brandvain, Yaniv and Schuchardt, Anita}, editor={Peters, Ove A.}, year={2020}, month=July, pages={e0236098} }

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse_3 v13.0
Redivis dataset DOI10.57761/gpg7-sg87
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v43.0