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, but are not limited to, structural equation modeling, multilevel modeling, intensive longitudinal analysis, psychometrics, Bayesian inference, network analysis, and machine learning. Successful
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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to statistical computing, Bayesian modeling, causal inference, clinical trials and analysis of complex large-scale data such as omics data, wearable tech, and electronic health record, with specific preference
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