options algorithm nr tolerance=1e-008 emtolerance=0.01 emiterations=250 nriterations=50 ; startvalues seed=0 sets=10 tolerance=1e-005 iterations=50 ; bayes categorical=0 variances=0 latent=0 poisson=0 ; quadrature nodes=11; standarderrors=standard; output parameters profile bvr; outfile 'word_97_out.sav' classification; variables dependent y1 probit, y2 probit, y3 probit, y4 probit, y5 probit, y6 probit, y7 probit, y8 probit, y9 probit, y10 probit, y11 probit, y12 probit, y13 probit, y14 probit, y15 probit, y16 probit, y17 probit, y18 probit, y19 probit, y20 probit, y21 probit; independent x; latent phi_s continuous, phi_n continuous; //Note: LG models p(Y>k), which reverses the signs for symmetric dist// equations phi_s; phi_n; y1 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y2 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y3 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y4 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y5 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y6 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y7 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y8 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y9 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y10 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y11 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y12 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y13 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y14 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y15 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y16 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y17 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y18 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y19 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y20 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ; y21 <- 1 + x + (-1)phi_s x + (-1)phi_n x + (1)phi_n ;