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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? |
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You use the loglikelihood values for the 2 models and compute a chi-square test from that as twice the loglikelihood difference. |
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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? |
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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 |
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Thanks! And how do I define the number of parameters in an LCGA? And specifically in my study with 6 cohorts? |
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The number of parameters is printed in your output. |
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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? |
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Q1: No. Q2: That is what you need. |
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