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Common methods for missing data in marginal structural models: What works and why

Electronic health records (EHR) are useful for addressing health-related questions, such as estimating the marginal effect of treatment over a long period of time. In practice, a patient’s treatment exposure may not be constant over time but it get updated as their medical history evolves. In turn, the new treatment may affect future health events and individual factors, potentially associated with the outcome of interest.

Machine learning brings an early diagnostic for pancreatic cancer a step closer to reality

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