LPA predicting growth factors? PreviousNext
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 Rebecca Shearer posted on Saturday, July 24, 2010 - 1:04 pm
Hi, I have estimated independently a 6-class LPA which fits well and a growth model of math and litercy which fits well. Is it possible to simultaneously estimate both in the same model? (e.g., estimate the LPA and then see whether the classes predict the intercept and slope for math and literacy within the same model?) I know it is problematic to output class membership and use it a second model since children do not 100% belong to classes (e.g., either output the class membership and enter these into a growth model). I just saw Logan & Petscher (2010) do this in a recent paper "School profiles of at-risk student concentration: Differential growth in oral reading fluency" Journal of School Psychology-- any suggestions would be greatly appreciated. Thank you
 Linda K. Muthen posted on Saturday, July 24, 2010 - 2:36 pm
Yes, this is possible. See the following paper which is available on the website:

van Lier, P.A.C., Muthén, B., van der Sar, R.M. & Crijnen, A.A.M. (2004). Preventing disruptive behavior in elementary schoolchildren: Impact of a universal classroom-based intervention. In Journal of Consulting and Clinical Psychology, 72, 467-478.
 Rebecca Shearer posted on Saturday, July 24, 2010 - 3:51 pm
thank you so very much!
 Rebecca Shearer posted on Tuesday, July 27, 2010 - 6:12 pm
I read through the article you suggested, do you know if there is an example of how to combine the code for the mixture model (LPA) and the growth model? Or if I should get in touch directly with the author of the paper? Thank you in advance for your help. (I have been trying to combine the 2 codes and end up estimating a growth mixture model, which is not my intent!)
 Linda K. Muthen posted on Tuesday, July 27, 2010 - 6:34 pm
You can either send your attempt to support or contact the author. Be sure you have a different categorical latent variable for the LPA and the growth.
 Rebecca Shearer posted on Tuesday, July 27, 2010 - 11:11 pm
ok thank you again
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