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- W2240752212 abstract "The most widely used model in multinomial ordinal regression is the socalledcumulative multinomial model. In this work, we extend the tools fordetecting influential observations given by Cook (1977) and Johnson (1985)to the cumulative multinomial model. Cook´s statistic is commonly used forthe detection of influential observations in regression analysis. It is an overallmeasure of the change in the parameter estimates when one or more observationsare deleted from the data set. Originally, it was developed for normal linearregression models. However, it has been extended to generalized linear modelsas well. We give a further generalization based on divergence measures. On theother hand, Johnson proposed measures for detecting influence relative to thedetermination of probabilities for logistic regression. We extend these here tothe cumulative multinomial model. Finally, the relationships among measuresare indicated." @default.
- W2240752212 created "2016-06-24" @default.
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- W2240752212 date "2007-01-01" @default.
- W2240752212 modified "2023-09-24" @default.
- W2240752212 title "Influence Measures for Cumulative Multinomial Models: A point of view based on Divergence measures" @default.
- W2240752212 hasPublicationYear "2007" @default.
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