大阪大学　数理・データ科学教育研究センター
Center for Mathematical Modeling and Data Science,Osaka University

3MPCA applied to clinical longitudinal data and Bayesian estimation for the efficacy of antidepressants

Rei Monden (University of Groningen)

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4. 3MPCA applied to clinical longitudinal data and Bayesian estimation for the efficacy of antidepressants

大阪大学 数理・データ科学セミナー データ科学セミナーシリーズ 第26回(One-Day Seminar)

3MPCA applied to clinical longitudinal data and Bayesian estimation for the efficacy of antidepressants

Rei Monden (University of Groningen)

I will give a presentation about the studies where I applied Three-mode Principal Component Analysis (3MPCA) to clinical data. More specifically, 3MPCA was applied to various longitudinal datasets collected from Major Depressive Disorder patients. 3MPCA decomposes depression into homogeneous entities, while accounting for the interactions between different sources of heterogeneity, which shows the utility of the technique to investigate the underlying structure of complex psychopathology data and could help future development of better empirical depression subtypes. As a side, I will give a presentation about Bayesian approach to evaluate efficacy of FDA-approved antidepressants.