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Quality assurance of cognitive assessments and other categorical data
RISE - Research Institutes of Sweden, Safety and Transport, Measurement Science and Technology.ORCID iD: 0000-0002-3700-3921
RISE - Research Institutes of Sweden, Safety and Transport, Measurement Science and Technology.ORCID iD: 0000-0003-4349-500x
2019 (English)Conference paper, Oral presentation with published abstract (Other academic)
Abstract [en]

Did you ever wonder how to account for biases such as ceiling eects in your (cognitive) data?

Metrological quality assurance of human-based responses is in its infancy and analyzing categorial data and other human responses is challenging. However, there is a need to tackle those challenges to ensure that decisions about health care are made correctly. Quality assured comparability, interoperability and decision-making can successfully be done by applying sound metrological approaches to enable traceability as well as stressing declaration of measurement uncertainties. In the seminar, we present metrological approaches to ensure quality assurance of categorical data,such as cognitive assessments and other human-reported responses. This is followed by a hands-onworkshop where you are welcome to bring your own or freely available data for analyses.

Place, publisher, year, edition, pages
2019.
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:ri:diva-37325OAI: oai:DiVA.org:ri-37325DiVA, id: diva2:1280795
Conference
Charité lecture series,Thursday, 17.01.2019 CCM, Virchowweg 24, Aufgang B, Seminar Room 03.006
Projects
EMPIR 15HLT04 NeuroMet
Funder
EU, FP7, Seventh Framework Programme, EMPIR 15HLT04Available from: 2019-01-21 Created: 2019-01-21 Last updated: 2019-01-21Bibliographically approved

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Melin, JeanettePendrill, Leslie

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