Diagnostic procedures

Joseph W. McKean, Simon J. Sheather

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Diagnostic procedures are used to check the quality of a fit of a model, to verify the validity of the assumptions behind the model, and to find outlying and/or highly influential observations. Our discussion focuses on the linear model (the most widely used model). Much of our discussion, however, pertains to other models, as we show when we extend our discussion to mixed models at the end of the paper. The traditional fit, least squares (LS), can be severely impaired by just one outlier. So along with LS we present two robust fits and diagnostic procedures which explore the differences among the three fits. These comparisons generally find the outlying and influential cases. Armed with this methodology, we then proceed to discuss diagnostics that explore the quality of fit and verify the validity of the assumptions, including independent and identically distributed errors and normality.

Original languageEnglish
Pages (from-to)221-233
Number of pages13
JournalWiley Interdisciplinary Reviews: Computational Statistics
Issue number2
StatePublished - 2009

ASJC Scopus subject areas

  • Statistics and Probability


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