In regression modeling, influential points are observations that, individually, exert large effects on a model’s results—the parameter estimates (\(\hat{\beta_0}, \hat{\beta_1}, …, \hat{\beta_j}\)) and, consequently, the model’s predictions (\(\hat{y_1}, \hat{y_2}, …, \hat{y_i}\)). Influential points aren’t necessarily troublesome, but observations flagged as highly influential warrant follow-up. A large value on an influence measure can signal anything from […]