A brief introduction to influence diagnostics in regression

Statistical analyses that involve regression methods often encounter data in which some observations have substantial influence. This article presents a nontechnical discussion of influence and of two techniques, based on leaving out each individual observation in turn, for diagnosing influential data. An example illustrates the techniques in an analysis of recurrence rates in endoscopic treatment of bleeding peptic ulcers.