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? Set the panel definition
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SETPANEL    ; Group = id ; Pds = ti $
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? Define the variables in the model
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NAMELIST    ; XC = the variables in your model $
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? After estimation, compute partials
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PARTIALS    ; If [ ti = 7 ] ; Effects: XC ; Summary $
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? Two part model
? We used X2=one,married,hhkids.)
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NAMELIST    ; X2 = your variables $   (Choose 2 or 3, not including female)
HISTOGRAM   ; Rhs=DocVis $  (Just to see the problem)
POISSON     ; Lhs = DocVis ; Rhs = X ; Hurdle ; Rh2 = X2 ; Table=Hurdle$
CREATE      ; lh = logl_obs $
POISSON     ; Lhs = DocVis ; Rhs = X; Zip ; Rh2 = X2;  Table=zip$
CREATE      ; lz = logl_obs $
MAKETABLE   ; hurdle,zip $
CALC        ; Tsd ( lh,lz)  $
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? Random parameters Model
? Latent Class
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CREATE      ; docvis12  =  docvis ~ 12 $
NAMELIST    ; XP = ... the variables in your main equation $  
NAMELIST    ; XH = ... the variables in your hurdle equation $  
POISSON     ; Lhs = DocVis12 ; Rhs = XP $
POISSON     ; Lhs = DocVis12 ; Rhs = XP ; LCM ; Pts = 2 ; Panel $
POISSON     ; Lhs = DocVis12 ; Rhs = XP ; Rh2 = XH ; Hurdle $
CREATE      ; pclass1 = classp_i (group,1) $
CREATE      ; class1 = pclass1 > .5 $
DSTAT       ; Rhs = Docvis12 ; Str = class1 $
CALC        ; Tst(docvis12,class1) $  (Tests whether means are different in the two groups)
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? Fixed effects NB Model
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POISSON     ; Lhs = docvis12 ; Rhs = your XP list $
POISSON     ; Lhs = docvis12 ; Rhs = your XP list ; Panel ; Fixed $
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? Random parameters
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? Set the panel as usual if you have not done so already in this session.
? This step is necessary for the Count data and ordered choice models
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MODEL       ; Lhs = ... ; Rhs = a set of variables $  (Fit the pooled model, no options.)
MODEL       ; Lhs = ... ; Rhs = a set of variables
            ; RPM ; Halton ; Pts = 50 ; Panel ; Parameters ; Maxit = 20 
            ; Fcn = variable (n), variable (n), ...  $
MATRIX      ; beta_fem = beta_i(1:7293,2:2) $
KERNEL      ; Rhs = beta_fem ; Title=Distribution of E[beta_fem] Across Sample $