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title: "Causal roadmap tutorial applied to the case study of an AKI safety signal"
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# Causal Roadmap Tutorial

Welcome to the **Causal Roadmap Tutorial**.  
This section walks through three major steps of the causal inference roadmap using an **acute kidney injury (AKI) case study** comparing sofosbuvir-containing vs non-sofosbuvir antiviral regimens.

Each chapter corresponds to a key step of the causal roadmap:

1. [Step 1a – Causal Question and Causal Estimand](step1_causal_estimand.qmd)  
   Defining the causal question and selecting the estimand under the ICH E9(R1) framework.

2. [Steps 1b–2 – Causal Model and Observed Data](step2_causal_model.qmd)  
   Building the causal model, DAG, and mapping variables from the data-generating process.

3. [Step 3 – Identification and Causal Assumptions](step3_identification.qmd)  
   Linking the causal estimand to the observed data through identification assumptions.

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## About This Tutorial

These materials are designed to teach the first steps of the **Causal Roadmap** in a regulatory-grade RWE analysis.  
The content aligns with the ICH E9(R1) estimand framework and follows a target trial emulation approach.

By the end of this section, you will be able to:

- Define a causal question that aligns with clinical intent.  
- Identify estimands suitable for post-market safety evaluation.  
- Understand how causal assumptions translate into statistical estimators.

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