See -h mlogit-. BTW, why would you want to reduce the information of a
continuous variable in 1 and 2? In 3., it is clear that industries should be
represented by a discrete measures, I 1. and 2. It is more difficult to see
why you want the quintiles and not the variable itself...
HTH
Martin
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Richard Harvey
Sent: Wednesday, September 24, 2008 12:37 PM
To: [email protected]
Subject: st: predictive regression with mutiple dependent variable
Hi all,
I am trying to build a model for predicting the probability of a firm
falling into either one of four seperate classes (the dependent
variable) using several independent variables.
Lets say the groups are G B U and S.
now the independet variables consists of
1. a variable which can take a value of 1 to 5. This variable is
created by sorting all the units based on this variable and putting
then into quintiles.So this number represents the quintile it belongs
to.
2. is similar to variable 1, can take of 1 to 5, this is created on
quintiles of another measure
3. represents the industry (there are 5 broad industry groupings)
4. 3 other continous variables
5. Some of the variables in 3 may have been affected by the state of
the economy during ceratin periods. So time or state of economy should
somehow be factored in. But i am not sure how a varaible for year
will work in the context of a prediction model. I suppose it will then
have to be a variable representing the state of the economy.
and the rest are all continous variables
What model should i be looking at?
--
thanks for your time
rich
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