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I have 12 data points (T1T12) and would like to model for potential cubic growth in GMM. I managed to fit a decent linear and quadratic growth models but am unclear on to determine the appropriate times in the syntax for a cubic model: i s  T1@0 T2@1 T3@2 T4@3.........T12@11 i s q  T1@0 T2@.01 T3@.04 T4@.09......T12@1.21 What would the appropriate syntax time be for a cubic model? i s q cub  T1@? T2@?..........T12? Thank you for your assistance. 


Yes, just add a fourth growth factor. 


Thanks for the quick response. Can you clarify exactly what you mean though. As shown in my initial post I already have four growth factors listed (i s q cub) before the "" symbol, but I am unclear on what I should list after the "@" symbol for each of the 12 time points. Thank you for your explanation. 


You list the linear time scores after the  symbol. I just noticed you did this incorrectly for the quadratic model. The time scores are always the linear and Mplus computes the others. Keep the on a small scale like 0 .1 .2 etc. 


Thank you for the clarification. It looks like I was making this more complicated than needed. I really appreciate your help. 


I have 7 data points and would like to investigate various forms of growth (linear, quadratic, cubic). I wondered what would be the best way to do this, that is: is there a specific order to introduce the various growth factors? So first try linear, than linear and quadratic, and so on? (and then check whether mean and variance of the growth factors are different from zero) Or should I be guided by other things? 


Could someone help me with this question? Thank you in advance. 


If theory can't guide you, yes, first try linear, than linear and quadratic, and so on and then check whether mean and variance of the growth factors are different from zero. 


Thank you for your reply. If I understand correctly, this could imply that e.g. a linear, quadratic AND cubic growth factor are needed when all of means and/or variances are different from zero? 


Right. 


Are 7 time points enough to model potential cubic growth? Or should such a model preferably include more measurement points?/isn't there a minimum number of measurement points to consider cubic growth 


Four time points is enough for quadratic so I think a cubic model can be identified for seven time points. You will get a message if not. 


Okay thank you. Would this also be true for a model with only 5 data points? I think that might really be too few data points to model cubic growth but I'm not sure. 


(I believe I remember Bengt Muthen mentioning in another thread that he wouldn't bother using cubic growth for a model with only 4 data points so maybe this also applies to 5 data points) 


5 data points isn't really enough for a cubic. 

Mollie Marr posted on Thursday, November 09, 2017  2:33 pm



Could you provide a bit more information on why 5 data points would not be enough to include a cubic term? We have 5 data points and get a good model fit when we include a cubic term (the shape appears to be cubic). Would this mean we have over fitting? 


It is certainly doable but perhaps not very convincing as a growth form  perhaps not much power to reject the model as you would have with more time points. 

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