? Using the clogit.lpj data
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? 1. Multinomial Probit Model
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NLOGIT  ; Lhs = Mode ; output=ic
	  ; Choices = Air,Train,Bus,Car
        ; Rhs = TTME,INVC,INVT,GC; Rh2=One,Hinc $
        ; Effects:GC(*) $
NLOGIT  ; Lhs = Mode ; MNP ; PTS = 10 ; Maxit = 10 ; Halton
	  ; Choices = Air,Train,Bus,Car
        ; Rhs = TTME,INVC,INVT,GC; Rh2=One,Hinc 
        ; Effects:GC(*) $
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? Using Brand Choices Data, brandchoicesSP.lpj
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?(1) Basic 3 class model
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Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None
       ; Rhs = Fash,Qual,Price,ASC4
       ; LCM ; Pds = 8 ; Pts = 3 $
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? (2) 3 class model. Class probabilities depend on covariates
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Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None
       ; Rhs = Fash,Qual,Price,ASC4
       ; LCM=Male,Age25,Age39 ; Pds = 8 ; Pts = 3 $
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? (3) Overspecified model.  4 class model.  The true model
?     underlying the data has three classes
Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None
       ; Rhs = Fash,Qual,Price,ASC4
       ; LCM ; Pds = 8 ; Pts = 4 $
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? (4) Random parameters model
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Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None
       ; Rhs = Fash,Qual,Price,ASC4
       ; RPL  ; Fcn= Fash(n),Price(n) 
       ; Pds = 8 ; Pts = 25 $
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? (5) Correlated parameters
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Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None
       ; Rhs = Fash,Qual,Price,ASC4
       ; RPL  ; Fcn= Fash(n),Price(n) ; Correlated
       ; Pds = 8 ; Pts = 25 $
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? (6).  An Error Components Logit model
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ECLOGIT ; Lhs = Choice ; Choices = Brand1,Brand2,Brand3,None
        ; Rhs = Fash,Qual,Price,ASC4 
        ; Pts = 10 ; Pds = 8
        ; ECM = (Brand1,Brand2,Brand3),(none) $