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st: Help with mlogit questions; IIA; choosing outcome variables; collapsing outcomes, multinomial logistic regression

From   Tomas M <>
Subject   st: Help with mlogit questions; IIA; choosing outcome variables; collapsing outcomes, multinomial logistic regression
Date   Wed, 13 May 2009 12:53:20 -0700

Hello Statalisters,

Thank you in advance for your replies.

I have a question regarding mlogit (multinomial logistic regression).


Suppose I have 5 outcome variables, (e.g. blue collar, menial, craft, white collar, prof, etc.).

I have read Chapter 6 of Long and Freese's Categorical Data Analysis text.

Regarding the section on Checking the categories (i.e. outcomes) on the left side of the model, and determining if they can be collapsed (i.e. collapsing the outcome variables into blue collar, white collar, and professional), it says to run -mlogtest, combine- or -mlogtest, lrcomb-.  These test the null hypothesis that "Coefficients except intercepts associated with given pair of alternatives are 0 (i.e. alternatives can be combined)".


Suppose that the mlogtests give results that suggest that the alternatives (i.e. outcomes) CAN be combined (i.e. gives a high p-value for evidence for the null, as stated above), does this mean that if we choose to combine the alternatives, we can do so in the model? (if we choose to combine them based on our knowledge of the data, etc.).

Or does this mean that we SHOULD combine the alternatives?


Suppose I have the following outcome variables: blue collar, white collar, professional, no job.

How would I go about deciding whether to include "No job" as an outcome in my models?

Suppose that having "No Job" included in my models, versus having it excluded, makes no difference to the estimated coefficients.  What justifications should I use to decide whether to include "No Job" or exclude it?  Is this solely a decision based on my own knowledge of the data, and whether or not it would be of interest to the readers?

Does the assumption of independence of irrelevant alternatives (IIA) have anything to do with this justification?  I.e., if all of my outcomes satisfy this assumption (after running the Hausman and/or Small-Hsiao tests), and they are distinct and dissimilar, then it does not matter if I include "No Job" or not (and thus my choice for including or excluding it rests solely on my decisions as an analyst)?

Thank you very much,


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