Influence diagnostics refers to a set of techniques used to identify and assess the impact of individual data points on the overall results of a statistical model. By determining how much a specific observation affects the model's estimates and predictions, analysts can make more informed decisions about the validity and reliability of their model. This process is crucial in model building strategies as it helps to ensure that the results are not unduly influenced by outliers or leverage points that may distort the findings.
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