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I want to do LCGA with a cohortsequential design. I ran LCGA's with slope and intercept constrained and unconstrained, but I don't get a chiČ value. classes=C(6); knownclass = C(cohort=1 cohort=2 cohort=3 cohort=4 cohort=5 cohort=6); model: %overall% I S  LAC1@0 LAC2@1 LAC3@2 LAC4@3; I; S; I with S; %c#1% [I] (1); [S] (2); %c#2% I S  LAC2@1 LAC3@2 LAC4@3; [I] (1); [S] (2); %c#3% I S  LAC1@1 LAC2@2 LAC3@3 LAC4@4; [I] (1); [S] (2); %c#4% I S  LAC1@2 LAC2@3 LAC3@4; [I] (1); [S] (2); %c#5% I S  LAC1@3 LAC2@4; [I] (1); [S] (2); %c#6% I S  LAC1@4; [I] (1); [S] (2); How do I get a chiČ to compare the models through chiČ difference test? 


You use the loglikelihood values for the 2 models and compute a chisquare test from that as twice the loglikelihood difference. 


So from this part of the output of each model? Loglikelihood H0 Value 15474.940 H0 Scaling Correction Factor 1.8329 for MLR I also found this: https://www.statmodel.com/chidiff.shtml But I don't get a loglikelihood for H1 with LCGA, only when I do LCGM. In that formula, would L0 be the logelikelihood of the constrained model and L1 of the unconstrained model? Or do I need to use another formula? 


You use the H0 logL value for each of the two models and use the link you give but go to the heading Difference Testing Using the Loglikelihood 


Thanks! And how do I define the number of parameters in an LCGA? And specifically in my study with 6 cohorts? 


The number of parameters is printed in your output. 


Do I need to specify something in the output command to see the number of parameters? All I find now is the number of freely estimated parameters: I assume that is not what I need? 


Q1: No. Q2: That is what you need. 

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