My only advice is marginal to your main question.
The term "polychotomous", although common in the
literature, is malformed and based on a misparsing
of the word "dichotomous", whose elements
are "dicho" and "tomous". The term "polytomous",
also common in the literature, is more nearly correct.
Help stamp out this linguistic monstrosity!
Nick
[email protected]
N.B. this is a different kind of argument from
those in favour of "heteroskedasticity" rather than
"heteroscedasticity". In the latter case, there are
plenty of precedents for rendering the Greek letter
kappa into the English letter c, so one could be
sceptical about that argument.
"polychotomous" just got into the literature because someone
didn't understand the etymology of "dichotomy" and other people
copied that mistake. It's still wrong.
Ngo,PT, a.k.a. Thi Minh
Sorry to bother you again for the second time in the day!
I would like estimate a polychotomous logistic model using
mlogit. The main explanatory variable (say X) I use is
endogenous and in binary models, I have used IVs using the
ivprob command. How would one go about estimating
polychotomous logistic model with an endogenous variable for
which I have an instrument? I am interested in getting the
relative risk ratio as I am trying to differentiate the
impact X on the various discrete categories of Y on the left
hand side.
Any advice would be really appreciated. It is the first time
I am using logit/probit and
polychotomous models.
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