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RE: st: Thinking through best way to do a longitudinal analysis


From   "Polis, Chelsea B." <cpolis@jhsph.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Thinking through best way to do a longitudinal analysis
Date   Mon, 17 Aug 2009 09:09:11 -0400

Cameron, you are a wealth of information.  Thank you very much for these references!

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Cameron McIntosh
Sent: Sunday, August 16, 2009 5:59 PM
To: STATA LIST
Subject: RE: st: Thinking through best way to do a longitudinal analysis

Chelsea,

I don't see anything wrong with estimating and having a look at the individual latent slope trajectories, but I don't know the code offhand for requesting this in Stata. (In Mplus I believe this would be done by Bayesian factor score estimation). Perhaps -gllamm- has a similar approach. Have a look at the sections dealing with growth mixture models in:

Rabe-Hesketh, S. & Skrondal, A. (2008). Multilevel and Longitudinal Modeling Using Stata (2nd ed.).  College Station, TX: Stata Press.

Or perhaps someone here knows that code. Also, here are some other references that might help familiarize you with the logic of GMM, as well as give you some ideas for dealing with your missing data problems:

Muthen, B.O., & Asparouhov, T. (2008). Growth mixture modeling: Analysis with non-Gaussian random effects. In Fitzmaurice, G., Davidian, M., Verbeke, G. & Molenberghs, G. (eds.), Longitudinal Data Analysis (pp. 143-165). Boca Raton: Chapman & Hall/CRC Press.

Siddique, J., Brown, H.C., Hedeker, H., Duan, N., Gibbons, R.D., Miranda, J., and Lavori, P.W. (2008). Missing data in longitudinal trials - part B, analytic issues. Psychiatric Annals, 38, 793-801.

Beunckens, C., Molenberghs, G., Verbeke, G., and Mallinckrodt, C. (2008). A latent-class mixture model for incomplete longitudinal Gaussian data. Biometrics, 64, 96-105.

Dantan, E., Proust-Lima, C., Letenneur, L., and Jacqmin-Gadda, H. (2008). Pattern mixture models and latent class models for the analysis of multivariate longitudinal data with informative dropouts. The International Journal of Biostatistics, 4, 1-26.

Roy, J. (2003). Modeling longitudinal data with nonignorable dropouts using a latent dropout class model. Biometrics, 59, 829-836.

Cam
----------------------------------------
> From: cpolis@jhsph.edu
> To: statalist@hsphsun2.harvard.edu
> Date: Sun, 16 Aug 2009 16:23:11 -0400
> Subject: RE: st: Thinking through best way to do a longitudinal analysis
>
> Thanks so much to both of you for the suggestions and all of these great references! I will download all of these articles and read them. In the meantime, do you think calculating individual slopes is a bad idea? If not, do you know how I might go about doing this in STATA?
>
> Thank you!
> Chelsea


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