Ordinal Logistic Regression | JMP 13.2

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Fitting Linear Models • Logistic Regression Models • Logistic Regression Overview • Ordinal Logistic Regression

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Ordinal Logistic Regression

When the response variable has an ordinal modeling type, the platform fits the cumulative response probabilities to the logistic function of a linear model using maximum likelihood. Therefore, the cumulative probability of being at or below each response level is modeled by a curve. The curves are the same for each level except that they are shifted to the right or left.

Tip: If there are many response levels, the ordinal model is much faster to fit and uses less memory than the nominal model.

For more information about fitting models with ordinal response variables, see Ordinal Responses in Statistical Details.

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Help created on 9/19/2017