How Computational Modeling Can Force Theory Building in Psychological Science
2021/01/22 by Olivia Guest, Andrea E. Martin · 3 voices · 448 citations
Arts and Humanities · Mathematics · Neuroscience · Psychology · #Artificial intelligence #Causal inference #Cognitive science #Computational model #Computer science #Data science #Econometrics #Epistemology #Forcing (mathematics) #Functional Brain Connectivity Studies #Inference #Management science #Mathematics #Mental Health Research Topics #Philosophy and History of Science #Philosophy of science #Process (computing) #Psychology #Variety (cybernetics)
paper · open access · doi:10.1177/1745691620970585
published in Perspectives on Psychological Science 16(4), 789-802 (SAGE Publishing)
openalex publication_date 2021/01/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
Abstract
Psychology endeavors to develop theories of human capacities and behaviors on the basis of a variety of methodologies and dependent measures. We argue that one of the most divisive factors in psychological science is whether researchers choose to use computational modeling of theories (over and above data) during the scientific-inference process. Modeling is undervalued yet holds promise for advancing psychological science. The inherent demands of computational modeling guide us toward better science by forcing us to conceptually analyze, specify, and formalize intuitions that otherwise remain unexamined—what we dub open theory. Constraining our inference process through modeling enables us to build explanatory and predictive theories. Here, we present scientific inference in psychology as a path function in which each step shapes the next. Computational modeling can constrain these steps, thus advancing scientific inference over and above the stewardship of experimental practice (e.g., preregistration). If psychology continues to eschew computational modeling, we predict more replicability crises and persistent failure at coherent theory building. This is because without formal modeling we lack open and transparent theorizing. We also explain how to formalize, specify, and implement a computational model, emphasizing that the advantages of modeling can be achieved by anyone with benefit to all.
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Discussions
- There's even more zooming like Guest, O. & Martin, A. E. (2021). How Computational Modeling Can Force Theory Building in Psychological Science. Perspectives on Psychological Science. doi.org/10.1177 [bsky, 20 points, 2 comments]
- 4. Are computational models the answer? Guest, O., & Martin, A. E. (2020). How computational modeling can force theory building in psychological science. Perspectives on Psychological Sciences, 16(4), [bsky, 4 points, 1 comments]
- All in all, this ties in nicely with the previous papers we discussed, e.g. Guest & Martin (2021) doi.org/10.1177/1745... , Guest (2024) doi.org/10.1007/s421... [bsky, 1 points, 0 comments]
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