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determining if one factor directly affects another

Causal inference is the process of determining whether a cause-and-effect relationship exists between two variables. For example, in the context of hair loss (alopecia), researchers might use causal inference to determine if a specific treatment directly leads to hair regrowth. This involves using statistical methods and study designs, such as randomized controlled trials, to rule out other factors and establish a direct link.

Related Terms

• Correlation
• Causality
• Statistical Inference
• Causal Analysis
• Social Interactions
• Instrumental Variable Analysis
• Mendelian randomization