Article

Bias by Variance: How Common Parameter Transformations in Hierarchical Modeling Distort Group-Level Estimates

2026-07-14

Abstract excerpt

<p>Hierarchical modeling is widely used to simultaneously estimate group- and individual-level parameters in computational models of cognitive processes. When model parameters are bounded within a particular range, it is common practice to estimate the group-level parameters on the unbounded real line and then map the estimated mean onto the desired bounded parameter range using a nonlinear transformation. We poin...

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Literature Corpus work: 1c8d5e5e-6920-51ad-a8eb-626150e8a226
DOI: 10.31234/osf.io/vc94q_v2

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