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A Bayesian Machine Learning Approach for Optimizing Dynamic Treatment Regimes
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Outgoing claims: the papers this work cites, builds on, or argues with.
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New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes
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Optimal Dynamic Treatment Regimes
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Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m‐Out‐of‐n Bootstrap Scheme
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Optimal Dynamic Regimes: Presenting a Case for Predictive Inference
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Additional file 1 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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Additional file 2 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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Additional file 3 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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Additional file 4 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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Additional file 5 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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Additional file 6 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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Additional file 7 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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Additional file 8 of A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
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