A joint modeling approach for longitudinal microbiome data improves ability to detect microbiome associations with disease

• Pamela N. Luna,

  Roles Conceptualization, Formal analysis, Methodology, Software, Validation, Visualization, Writing – original draft

  Affiliations Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America, Department of Statistics, Rice University, Houston, Texas, United States of America

  https://orcid.org/0000-0002-4584-6363

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• Jonathan M. Mansbach,

  Roles Conceptualization, Funding acquisition, Writing – review & editing

  Affiliation Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America

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• Chad A. Shaw

  Roles Supervision, Writing – review & editing

  * E-mail: cashaw@bcm.edu

  Affiliations Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America, Department of Statistics, Rice University, Houston, Texas, United States of America

  https://orcid.org/0000-0001-7267-5398

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