Learner, Practitioner & Teacher
Causal inference is important in healthcare observational studies because it allows researchers to determine whether a particular treatment or intervention has a causal effect on health outcomes. In healthcare, observational studies are often conducted when it is not possible or
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Causal inference is important in healthcare because it allows researchers, healthcare providers, and policymakers to understand the causal relationships between different factors and health outcomes. This is critical for developing effective interventions, improving patient outcomes, and optimizing healthcare resource allocation.
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1)Spurious Correlations: A statistical correlation with no causal implication. This is basically when a statistical correlation doesn’t imply causality. Here is an example – There is a huge correlation between the suicide rate and the amount of expenditure. But there
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