Partial residual plots in generalized linear models

R. Dennis Cook, Rodney Croos-dabrera

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


In this article we explore the structure and usefulness of partial residual plots as tools for visualizing curvature as a function of selected predictors x2 in a generalized linear model (GLM), where the vector of predictors x is partitioned as xT = (xT1, xT2). The GLM extension of ceres plots is discussed, but to a lesser extent. The usefulness of these plots for obtaining a good visual impression of curvature may be limited by the specified GLM, the link function, and the stochastic behavior of the predictors. Partial residual plots seem to work well when modeling is in a region where the conditional mean of the response given x stays well away from its extremes so that the link is essentially linear, and E(x1

Original languageEnglish (US)
Pages (from-to)730-739
Number of pages10
JournalJournal of the American Statistical Association
Issue number442
StatePublished - Jun 1 1998


  • CERES plots
  • Predictor transformations
  • Regression


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