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1. ML-DL-TEH ML-DL-TEH Public

   R and Python codes for estimating heterogeneous survival treatment effect via Machine/Deep Learning methods in observational studies.

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2. Variable-selection-w-missing-data Variable-selection-w-missing-data Public

   A general variable selection approach in the presence of missing data in both covariates and outcomes. This approach exploits the flexibility of machine learning modeling techniques and bootstrap i…

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3. JMSSM-CT JMSSM-CT Public

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4. SAMTx SAMTx Public

   R codes for a flexible Monte Carlo sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome.

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5. CIMTRare CIMTRare Public

   This project estimates the causal effects of multiple treatments with rare outcomes

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6. riAFTBART riAFTBART Public

   R codes to implement a flexible approach for causal inferences with multiple treatments and clustered survival outcomes.

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