Thank you Koen, I am interested in estimating the mean and std of the latent variable, and am comfortable setting some restrictions on the thresholds to do this. I am using QLIM as I believe it will do what I want. However if there is a better procedure to do this in SAS please let me know. The program I am using to understand what SAS is doing is below: ************************************************************************** * Sample program which simulates a basic data set, and uses the * restrict statement to allow estimation of the latent parameters **************************************************************************; * Simulates a single latent variable with specified mean and sd; data temp; call streaminit(235); nits = 200; latent_mean = 4; latent_sd = 1.1; do id = 1 to nits; latent_y = rand("normal",latent_mean,latent_sd); if latent_y < 1.5 then obs_likert_r = 1; else if latent_y < 2.5 then obs_likert_r = 2; else if latent_y < 3.5 then obs_likert_r = 3; else if latent_y < 4.5 then obs_likert_r = 4; else obs_likert_r = 5; output; end; * Plots the latent variable as a check of the simulation; proc sgplot data=temp; histogram latent_y; run; * Plots the "observed Likert Ratings" as a check of the conversion; proc freq data=temp; table obs_likert_r; run; * Runs QLIM with restrict statment; proc qlim data=temp; endogenous obs_likert_r ~ discrete (dist=Probit); model obs_likert_r = ; * Fits model with only intercept; restrict _limit2=2.5; restrict _limit4=4.5; run; The output for the parameter estimates: Parameter EstimatesParameter DF Estimate StandardError t Value ApproxPr > |t|Intercept_Limit2_Limit3_Limit4Restrict1Restrict2 1 3.856617 0.082268 46.88 <.0001 1 2.500000 0 . . 1 3.665176 0.080374 45.60 <.0001 1 4.500000 0 . . -1 10.684632 6.768865 1.58 0.1147* -1 9.731302 6.900138 1.41 0.1590* In this example, the estimate of the intercept is reasonable, but not as good as I would like. The thresholds make sense But I am not sure what the Restrict statements refer to as they are not part of the model. Thank you for your thoughts. Dan
... View more