Multinomial logistic regression: Difference between revisions

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As a set of independent binary regressions: sloppy notation, you’re not summing over one particular outcome, you’re summing over all possible outcomes
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This formulation is also known as the [[Compositional_data#Additive_logratio_transform|alrAdditive log ratio]] transform commonly used in compositional data analysis. IfIn weother exponentiateapplications bothit’s sidesreferred andto solveas for“relative therisk”.<ref>[https://www.stata.com/manuals13/rmlogit.pdf probabilities,Stata weManual get:“mlogit — Multinomial (polytomous) logistic regression”]</ref>
 
If we exponentiate both sides and solve for the probabilities, we get:
 
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