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Abstract
The multinomial logit model is the most widely used model for nominal multi-category responses. One problem with the model is that many parameters are involved, another that interpretation of parameters is much harder than for linear models because the model is non-linear. Both problems can profit from graphical representations. We propose to visualize the effect strengths by star plots, where one star collects all the parameters connected to one explanatory variable. In contrast to conventional star plots, which are used to represent data, the plots represent parameters and are considered as parameter glyphs. The set of stars for a fitted model makes the main features of the effects of explanatory variables on the response variable easily accessible. The method is extended to ordinal models and illustrated by several data sets.
Dokumententyp: | Paper |
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Publikationsform: | Submitted Version |
Keywords: | Glyphs, star plots, visualization, multinomial logit model, ordered response models |
Fakultät: | Mathematik, Informatik und Statistik > Statistik > Technische Reports |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
URN: | urn:nbn:de:bvb:19-epub-12880-1 |
Sprache: | Englisch |
Dokumenten ID: | 12880 |
Datum der Veröffentlichung auf Open Access LMU: | 04. Apr. 2012, 09:18 |
Letzte Änderungen: | 04. Nov. 2020, 12:53 |
Alle Versionen dieses Dokumentes
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Visualization of Categorical Response Models - from Data Glyphs to Parameter Glyphs. (deposited 15. Feb. 2012, 13:11)
- Visualization of Categorical Response Models - from Data Glyphs to Parameter Glyphs. (deposited 04. Apr. 2012, 09:18) [momentan angezeigt]