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Hi, If I am doing a MGA SEM where the full model has an interaction term (used type = random) and the simple model has the interaction term (used type = general), how do I do a model comparison since the full model's output does not include Chisquare Test of Model Fit info? 


Update questions: Am I correct to say I have 3 df given the below output, and I can do a loglikelihood difference Chi Square test by subtracting the absolute value of the LL of my full model from the LL of my simple model and use the critical Chisquare of 3 df to determine significance or not? As it stands, it looks to me that the interaction model is no worse a fitting model than the simple model? Does this even make sense to do this "general" a model comparison for a MGA SEM where Roman Catholics are set up as the reference group to which Mainline Protestants and Evangelicals are compared? Stine MODEL FIT INFORMATION (simple model) Number of Free Parameters 46 Loglikelihood H0 Value 6486.941 H1 Value 6388.825 Information Criteria Akaike (AIC) 13065.883 Bayesian (BIC) 13263.550 SampleSize Adjusted BIC 13117.529 (n* = (n + 2) / 24) MODEL FIT INFORMATION (Full model with interaction) Number of Free Parameters 49 Loglikelihood H0 Value 6484.429 Information Criteria Akaike (AIC) 13066.858 Bayesian (BIC) 13277.416 SampleSize Adjusted BIC 13121.872 (n* = (n + 2) / 24) 


2 times the loglikelihood difference is distributed as chisquare. Please limit posts to one window. 

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