Classification Efficiency of Multinomial Logistic Regression Relative to Ordinal Logistic Regression

Abstract Classification procedures are useful for the prediction of a response (or outcome) as a result of knowledge of the levels of one or more independent (or predictor) variables. The procedure is said to classify the (possibly multivariate) observation to a level of the response variable. An example might be the prediction of whether an individual will be well, suffer a nonfatal heart attack, or suffer a fatal heart attack. This prediction might be made on the basis of the levels of various independent variables, such as weight, blood pressure, and serum cholesterol, to name a few. The three response categories of the aforementioned example are ordinal. An example of three nonordered response categories might be as follows: well, death from heart attack, and death from cancer. There is some recent interest in ordinal classification procedures. It is reasonable to assume that, when the response variable is ordinal, inclusion of ordinality in the classification model to be estimated should improve mode...