In causal inference, a cutoff is a specific threshold that determines eligibility for treatment in studies using regression discontinuity designs. It separates observations into different groups based on whether they fall above or below this threshold, influencing the assignment of treatment. This concept is crucial for identifying causal effects by creating a quasi-experimental design where treatment effects can be estimated more accurately.
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