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.