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Effect Displays in R for Generalised Linear Models

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  • John Fox
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    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.

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    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 08 ()
    Issue (Month): i15 ()
    Pages:

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    Handle: RePEc:jss:jstsof:08:i15

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    Web page: http://www.jstatsoft.org/

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    Cited by:
    1. John Fox, . "The R Commander: A Basic-Statistics Graphical User Interface to R," Journal of Statistical Software, American Statistical Association, vol. 14(i09).
    2. John Fox & Jangman Hong, . "Effect Displays in R for Multinomial and Proportional-Odds Logit Models: Extensions to the effects Package," Journal of Statistical Software, American Statistical Association, vol. 32(i01).
    3. G. Guerra & R. Patuelli & R. Maggi, 2012. "Ethnic Concentration, Cultural Identity and Immigrant Self-Employment in Switzerland," Working Papers wp808, Dipartimento Scienze Economiche, Universita' di Bologna.

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