SweetPea: A standard language for factorial experimental design

Experimental design is a key ingredient of reproducible empirical research. Yet, given the increasing complexity of experimental designs, researchers often struggle to implement ones that allow them to measure their variables of interest without confounds. SweetPea ( https://sweetpea-org.github.io/...

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Bibliographic Details
Published in:Behavior research methods 2022-04, Vol.54 (2), p.805-829
Main Authors: Musslick, Sebastian, Cherkaev, Anastasia, Draut, Ben, Butt, Ahsan Sajjad, Darragh, Pierce, Srikumar, Vivek, Flatt, Matthew, Cohen, Jonathan D.
Format: Article
Language:English
Subjects:
Behavioral Science and Psychology
Cognitive Psychology
Computers
Humans
Language
Machine Learning
Nervous system
Psychology
Research Design
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Summary:Experimental design is a key ingredient of reproducible empirical research. Yet, given the increasing complexity of experimental designs, researchers often struggle to implement ones that allow them to measure their variables of interest without confounds. SweetPea ( https://sweetpea-org.github.io/ ) is an open-source declarative language in Python, in which researchers can describe their desired experiment as a set of factors and constraints. The language leverages advances in areas of computer science to sample experiment sequences in an unbiased way. In this article, we provide an overview of SweetPea’s capabilities, and demonstrate its application to the design of psychological experiments. Finally, we discuss current limitations of SweetPea, as well as potential applications to other domains of empirical research, such as neuroscience and machine learning.
ISSN:1554-3528
1554-3528
DOI:10.3758/s13428-021-01598-2