?================================================================ ? Load the panel probit project ?================================================================ ? (1) Random parameters approach to the random effects model. ? Random constant model ?-------------------------------------------------------- Sample;1-2000$ Namelist ; X = imum,fdium,logsales,sp,one$ Probit ; Lhs = IP ; Rhs = X ; Random ; Pds = 5 $ Probit ; Lhs = Ip ; Rhs = X ; RPM ; Fcn = One(n) ; Pts = 100 ; Pds = 5 $ Calc ; K1 = Col(X) + 1 $ Calc ; List ; SRP = B(K1) ; RhoRP = SRP^2 / (1 + SRP^2) $ ?-------------------------------------------------------- ? (2) Random parameters models ?-------------------------------------------------------- Sample ; All $ ? (a) Uncorrelated random parameters Probit ; Lhs = Ip ; Rhs = X ; RPM ; Fcn = imum(n),fdium(n) ; Pts = 25 ; Pds = 5 $ ? (b) Correlated random parameters Probit ; Lhs = Ip ; Rhs = X ; RPM ; Correlated ; Fcn = imum(n),fdium(n) ; Pts = 25 ; Pds = 5 $ ? (c) Random parameters with covariates in the means of the ? random parameters. Probit ; Lhs = Ip ; Rhs = X ; RPM = InvGood,ConsGood,Food ; Fcn = imum(n),fdium(n) ; Pts = 25 ; Pds = 5 ; Parameters $ ? (d) Examine conditional means of random parameters. Create ; Bimum = 0 ; Bfdium = 0 $ Namelist ; Bi = Bimum,Bfdium $ Sample ; 1 - 1270 $ Create ; Bi = Beta_i $ Kernel ; Rhs = Bimum $ ?-------------------------------------------------------- ? (3) Latent Class Models ?-------------------------------------------------------- Sample ; All $ Logit ; Lhs = IP ; Rhs = X ; LCM ; Pts = 3 ; Pds = 5 ; Parameters $ Logit ; Lhs = IP ; Rhs = X ; LCM = InvGood,Consgood,Food ; Pts = 3 ; Pds = 5 ; Parameters $ Sample;1-500$ Logit ; Lhs = IP ; Rhs = X ; LCM = InvGood,Consgood,Food ; Pts = 3 ; Pds = 5 ; Parameters ; List $