Matrix that contains values for each observation on the diagonal, known as
hat values, which represent the impact of the observed dependent variable on its predicted value. If all cases have equal influence, each would have a value of p/n, where p equals the number of independent variables + 1, and n is the number of cases. If a case has no influence, its value would be ‐1 ÷ n, whereas total domination by a single case would result in a value of (n ‐ 1)/n. Values exceeding 2p/n for larger samples, or 3p/n for smaller samples (n ≤ 30), are candidates for classification as influential observations.