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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 
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Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None
; Rhs = Fash,Qual,Price,ASC4 
; LCM ; Pds = 8 ; Pts = 4 $ 


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? (4) A model for attribute nonattendance 
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NLOGIT ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None 
; Rhs = Fash,Qual,Price,ASC4 
; LCM ; Pds = 8 ; Pts = 4 
; RST = b1,b2,b3,b4, b1, 0,b3,b4, 0,b2,b3,b4, 0, 0,b3,b4 $ 
NLOGIT ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None 
; Rhs = Fash,Qual,Price,ASC4 
; LCM ; Pds = 8 ; Pts = 4 
; RST = b1,b2,b3,b4, c1, 0,c3,c4, 0,d2,d3,d4, 0, 0,e3,e4 $ 


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? (5) Random parameters model 
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Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None 
; Rhs = Fash,Qual,Price,ASC4 $ 
CALC ; logl0 = logl $ 
Nlogit ; Lhs = Choice ; Choices=Brand1,Brand2,Brand3,None 
; Rhs = Fash,Qual,Price,ASC4 
; RPL ; Fcn= Fash(n),Price(n) 
; Pds = 8 ; Pts = 25 $ 
CALC ; logl1 = logl $ 
CALC ; List ; chisq = 2*(logl1 - logl0) $ 


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? (6) 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 = 10 $ 


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? (7) Willingness to Pay 
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RPLogit ; Lhs = Choice ; Choices = Brand1,Brand2,Brand3,None 
; Rhs = Fash,Qual,Price,ASC4 
; Fcn = Fash(n),Qual(o) ; Pds=8 ; Pts=10 
; WTP = Qual / Price ; Par $ 
Matrix ; wtp_i = -1*wtp_i $ 
Kernel ; Rhs = wtp_i 
; Title=Conditional Estimates of Willingness to Pay $ 

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? (8) 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) $