Design a study using Marginal Structural Models (MSM) to estimate causal effects in the presence of time-varying treatments.

Instruction: Outline the key steps in designing such a study and explain how MSM helps in adjusting for time-varying confounders.

Context: The question tests the ability to design robust causal inference studies using advanced statistical methods like Marginal Structural Models.

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Firstly, it's essential to clearly define the study's objective and identify the key variables, including the outcome, treatment, and confounders. For our discussion, let's consider the objective is to estimate the causal effect of a digital health intervention (the treatment) on patient health outcomes (the outcome) over a 12-month period. The confounders in this scenario could include patient demographics, health status, and behaviors that may change over time.

To address this, the study design would follow these steps:...

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