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The followings are the input and output I have. The program keeps saying that "CINDICATORS" option is unknown.... What's wrong with my syntax? INPUT INSTRUCTIONS Title: ALCOHOL Data: FILE IS C:\HKTEMP\ALC.DAT; TYPE IS INDIVIDUAL; FORMAT IS FREE; NOBSERVATIONS ARE 350; VARIABLE:NAMES ARE AFFDIS AUSE BUSE CUSE DUSE dis sex par neo paralc con; USEVARIABLES ARE DIS AUSE BUSE CUSE DUSE; MISSING=all(999); CLASSES=C(3); CATEGORICAL = DIS; ANALYSIS:TYPE=MIXTURE; MITERATIONS=500; MODEL: %OVERALL% I BY AUSE@1 BUSE@1 CUSE@1 DUSE@1; S BY AUSE@2 BUSE@1 CUSE@0 DUSE@1; [AUSE@0 BUSE@0 CUSE@0 DUSE@0]; i*7 s*.7; i with s*.5; C#1 BY DIS*8; C#2 BY DIS*4; C#3 BY DIS*6; %C#1% [I*1.3 S*.3]; %C#2% [I*2.3 S*.5]; %C#3% [I*3.3 S*.5]; Mplus VERSION 2.01 PAGE 2 Mplus VERSION 2.01 PAGE 3 Mplus VERSION 2.01 PAGE 4 *** ERROR in Model command C BY U statements are no longer supported. Please refer to Chapter 9 of the Mplus User's Guide on how to change these statements using the new language. MUTHEN & MUTHEN 11965 Venice Blvd., Suite 407 Los Angeles, CA 90066 Tel: (310) 3919971 Fax: (310) 3918971 Web: www.StatModel.com Support: Support@StatModel.com Copyright (c) 19982001 Muthen & Muthen 


The message from the output you sent, C BY U statements are no longer supported. Please refer to Chapter 9 of the Mplus User's Guide on how to change these statements using the new language. is telling you that the c BY u syntax has been changed in Version 2. If you refer to pages 132134 in Chapter 9 of the Mplus User's Guide, you will find the new syntax. You can also look at the mixture modeling examples on the website which show the new syntax. 


Dear Dr. Muthén, With a colleague we wanted to perform a LCA with a complex sample (teachers' ratings). We wrote the syntax: Variable: names are gender class teacher u1u25 x1x25 y1y25; usevariables = x2 x10 x15 x21 x25; categorical = x2 x10 x15 x21 x25; missing is blank; stratification is teacher; classes = c (2); Analysis: Type = Mixture Complex ; Starts = 500 10; Output: tech1 tech8 tech10 tech11; However the output is empty. The message is the following: INPUT READING TERMINATED NORMALLY LCA teacher SDQ complex sample Could you help us to clarify the problem. Thank you very much. Best regards, Robert 


Please send the input, data, output, and your license number to support@statmodel.com. 

socrates posted on Tuesday, November 22, 2011  11:26 pm



I built a LCA with 2 latent classes and ran this model in Mplus Version 3.11. So far, everything went well. However, when running exactly the same syntax with exactly the same dataset in Version 6.1, I get the following error message: THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY DUE TO AN INSUFFICIENT NUMBER OF E STEPS. INCREASE THE NUMBER OF MITERATIONS. ESTIMATES CANNOT BE TRUSTED. Why does this happen? P.S. The error message still appears after increasing the miterations up to 500,000. 


Please send the output and your license number to support@statmodel.com. 


Hi, I have an latent class model with 7 indicators, a continuous covariate and binary group. I am unsure how to construct the syntax to hold item response probabilties invariant over the groups, but leave the other parameters (latent statuses and covariate effects) to vary between the genders. Can you advise as to what the syntax should look like? Cheers, Oxnard 


It should look like Example 7.12 but without the direct effect from x to u4. 


A week or so ago, somebody asked about using TECH11 (LMR) and TECH14 (BLRT) to determine the number of latent classes. They were concerned about needing to have their largest class last. An Mplus Web Note No. 14 is now available and will shortly be posted that gives a detailed description of how to use these methods. The note describes the K1STARTS and LRTSTARTS options that go with TECH11 and TECH14. It points out that reordering the classes to have the largest class last is not necessary. Avoiding local optima by replication of the best loglikelihood value is discussed. The note also shows the value of the OPTSEED option. A 3step strategy is presented for doing the analyses successfully and with as little computational time as possible. 

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