Causal Inference Challenges
Navigating the complexities of causal inference can be daunting, especially when considering unmeasured confounders. Lucy discusses the importance of conducting tipping point sensitivity analyses to assess the robustness of results and encourages transparency about assumptions made during analysis. By explicitly stating potential confounders and their impacts, researchers can invite valuable insights from subject matter experts, ultimately advancing the field.In this clip
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Practical AI
A casual conversation concerning causal inference
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