Abstract
In large two-way tables an additive fit typically leaves too much discernable structure in the residuals. Multipolishing refers to the fitting of more complex models allowing for nonlinear effects of the factors and thus partially describing the interaction between the factors. This paper introduces multipolishing and shows how the two-way plots, familiar in the case of additive fits, can be adapted to these more general and more detailed descriptions of the data table. Additional ideas such as the fragmentation of data tables, the inclusion of residuals into the plots, or the visual comparison of different fits are briefly discussed.
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