Regularized Bayesian calibration and scoring of the WD-FAB IRT model improves predictive performance over marginal maximum likelihood

• Joshua C. Chang,

  Roles Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

  Affiliation Rehabilitation Medicine Department, NIH Clinical Center, Bethesda, Maryland, United States of America

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• Julia Porcino,

  Roles Writing – original draft, Writing – review & editing

  Affiliation Rehabilitation Medicine Department, NIH Clinical Center, Bethesda, Maryland, United States of America

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• Elizabeth K. Rasch,

  Roles Funding acquisition, Methodology, Resources, Supervision, Writing – original draft, Writing – review & editing

  Affiliation Rehabilitation Medicine Department, NIH Clinical Center, Bethesda, Maryland, United States of America

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• Larry Tang

  Roles Formal analysis, Methodology, Writing – original draft, Writing – review & editing

  * E-mail: liansheng.tang@ucf.edu

  Affiliations Rehabilitation Medicine Department, NIH Clinical Center, Bethesda, Maryland, United States of America, National Center for Forensic Science, University of Central Florida, Orlando, Florida, United States of America, Department of Statistics and Data Science, University of Central Florida, Orlando, Florida, United States of America

  https://orcid.org/0000-0002-7276-155X

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