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Effect Displays in R for Generalised Linear Models | Fox | Journal of Statistical Software
Authors: John Fox
Title: Effect Displays in R for Generalised Linear Models
Abstract: This paper describes the implementation in R of a method for tabular or graphical display of terms in a complex generalised linear model. By complex, I mean a model that contains terms related by marginality or hierarchy, such as polynomial terms, or main effects and interactions. I call these tables or graphs effect displays. Effect displays are constructed by identifying high-order terms in a generalised linear model. Fitted values under the model are computed for each such term. The lower-order "relatives" of a high-order term (e.g., main effects marginal to an interaction) are absorbed into the term, allowing the predictors appearing in the high-order term to range over their values. The values of other predictors are fixed at typical values: for example, a covariate could be fixed at its mean or median, a factor at its proportional distribution in the data, or to equal proportions in its several levels. Variations of effect displays are also described, including representation of terms higher-order to any appearing in the model.

Page views:: 46455. Submitted: 2003-04-29. Published: 2003-07-22.
Paper: Effect Displays in R for Generalised Linear Models     Download PDF (Downloads: 56604)
DOI: 10.18637/jss.v008.i15

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