Abstract
AbstractIn a statistical information theoretical setup, the logistic regression model has been extended to a generalized family of binary regression models that are scaled through the \(\phi \)-divergence [8]. Here, we introduce generalized families of models for ordinal responses. Such families of generalized models, though flexible, have not easily interpretable parameters. We propose simple measures that facilitate a straightforward interpretation for the effects of explanatory variables on a binary or ordinal response.
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