Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: John Fox, Sanford Weisberg
Title: Visualizing Fit and Lack of Fit in Complex Regression Models with Predictor Effect Plots and Partial Residuals
Abstract: Predictor effect displays, introduced in this article, visualize the response surface of complex regression models by averaging and conditioning, producing a sequence of 2D line graphs, one graph or set of graphs for each predictor in the regression problem. Partial residual plots visualize lack of fit, traditionally in relatively simple additive regression models. We combine partial residuals with effect displays to visualize both fit and lack of fit simultaneously in complex regression models, plotting residuals from a model around 2D slices of the fitted response surface. Employing fundamental results on partial residual plots along with examples for both real and contrived data, we discuss and illustrate both the strengths and limitations of the resulting graphs. The methods described in this paper are implemented in the effects package for R.

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Paper: Visualizing Fit and Lack of Fit in Complex Regression Models with Predictor Effect Plots and Partial Residuals     Download PDF (Downloads: 163)
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effects_4.1-0.tar.gz: R source package Download (Downloads: 9; 2MB)
v87i09.R: R replication code Download (Downloads: 11; 6KB)

DOI: 10.18637/jss.v087.i09

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.