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StatsToDo : Ordinal Logistic Regression Explained

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Introduction Example R Code Example Explained
This page provides explanations and example R codes for Ordinal Logistic Regression, which is one of the algorithms based on the Generalized Linear Models. It is a variant of the Multinomial Regression model, as explained in the Multinominal Logistic Regression Explained Page , but the dependent variable is ordinal, in that they are ordered in scale alphabetically, so the grp1<Grp2<Grp3 ...

In R, the independent variables can be measurements or factors

  • Measurements are numerical, and can be binary(0/1), ordinal, or parametric
  • Factors are text, and consists of group names. Unless otherwise assigned, R arrange group names alphabetically, and use the first name as the reference group
The algorithm produces m-1 formulae, m being the number of groups. The probabilities of belonging to the groups are estimated, and the estimated diagnosis assigned to that with the highest probability. Details on how this is carried out are described in the panel Example Explained

References

https://en.wikipedia.org/wiki/Ordered_logit

https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/