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Effect Displays in R for Generalised Linear Models

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  • Fox, John

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.

Suggested Citation

  • Fox, John, 2003. "Effect Displays in R for Generalised Linear Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i15).
    • Handle: RePEc:jss:jstsof:v:008:i15
    DOI: http://hdl.handle.net/10.18637/jss.v008.i15
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