What is it about?
This paper is about a course taught at CHI2023. The topic of the course is how to use a statistical method applied in Human-Computer Interaction (HCI) research. Structural equation modeling is a method to infer causal relationships from observational data. The course is tailored to HCI researchers and addresses the specifics of typical HCI study setups. The course provides access to free tools that also help with reproducibility of such research.
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Why is it important?
Research in HCI is often evaluated with statistical methods that do not reflect causal inference. The course helps promote these methods that help integrate theory and empirical findings in a more tight fashion. The tools we present are all open source and free to use and help researchers in creating reproducible results and preregistration.
Perspectives
We hope the course helps researchers to perform more solid research. The paper itself is a summary of a course taught at CHI2023 and will provide only a starting point for your research in SEM. If you are interested in hearing more about the content of the course please get in touch! We also have a course website at https://sem-in-r.github.io/chi2023-course-site/
André Calero Valdez
Universitat zu Lubeck
Read the Original
This page is a summary of: Structural Equation Modeling in HCI Research using SEMinR, April 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3544549.3574171.
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