@article{JSSv008i15,
title={Effect Displays in R for Generalised Linear Models},
volume={8},
url={https://www.jstatsoft.org/index.php/jss/article/view/v008i15},
doi={10.18637/jss.v008.i15},
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.},
number={15},
journal={Journal of Statistical Software},
author={Fox, John},
year={2003},
pages={1–27}
}