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From |
"Kieran McCaul" <Kieran.McCaul@uwa.edu.au> |

To |
<statalist@hsphsun2.harvard.edu> |

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

Date |
Mon, 17 Aug 2009 06:48:11 +0800 |

Hi Chelsea, I analysed some data a while ago which was collected from a large number of people (identified by the variable id) who had their aortic diameters (a_size) measured repeatedly over a number of time (years). The aim of the analysis was to examine the change in aortic diameter over time. I used GLMM for the final models, but initially one descriptive analysis that I ran simply calculated the slope and intercept of a regression fitted to each person in the data. I scatter plotted these. statsby inter=_b[_cons] slope=_b[years], by(id) clear: reg a_size years twoway scatter slope inter, msize(small) Kieran ______________________________________________ Kieran McCaul MPH PhD WA Centre for Health & Ageing (M573) University of Western Australia Level 6, Ainslie House 48 Murray St Perth 6000 Phone: (08) 9224-2701 Fax: (08) 9224 8009 email: Kieran.McCaul@uwa.edu.au http://myprofile.cos.com/mccaul http://www.researcherid.com/rid/B-8751-2008 ______________________________________________ If you live to be one hundred, you've got it made. Very few people die past that age - George Burns -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Polis, Chelsea B. Sent: Monday, 17 August 2009 4:23 AM To: statalist@hsphsun2.harvard.edu 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 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Cameron McIntosh Sent: Friday, August 14, 2009 10:36 PM To: STATA LIST Subject: RE: st: Thinking through best way to do a longitudinal analysis Chelsea, I'll try and point you in what I think might be a good direction. You may want to read up on growth mixture modeling: Wang, M., & Bodner, T.E. (2007). Growth Mixture Modeling: Identifying and Predicting Unobserved Subpopulations With Longitudinal Data. Organizational Research Methods, 10(4), 635-656. Dolan, C.V., Schmittmann, V.D., Lubke, G.H. & Neale, M.C. (2005). Regime switching in the latent growth curve mixture model. Structural Equation Modeling, 12, 94-119 http://users.fmg.uva.nl/cdolan/semmix.pdf Muthén, B.O. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D.Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345-368). Newbury Park, CA: Sage. In this case you "know" your "latent classes" (hormonal contraception or not), but that's no problem. The varying assessment times and missing data could be a bit tricky but there is some literature out there: Blozis, S.A., & Cho, Y.I. (2008). Coding and centering of time in latent curve models in the presence of interindividual time heterogeneity. Structural Equation Modeling, 15(3), 413-433. Biesanz. J.C., Deeb-Sossa, N., Papadakis, A.A., Bollen, K.A., Curran, P..J. (2004). The role of coding time in estimating and interpreting growth curve models. Psychological Methods, 9(1), 30-52. http://www.unc.edu/~curran/pdfs/Biesanz,Deeb-Sossa,Papadakis,Bollen&Curran(2004).pdf Duncan, S.C., & Duncan, T.E. (1994). Modeling incomplete longitudinal substance use data using latent variable growth curve methodology. Multivariate Behavioral Research, 29(4), 313-338. -gllamm- might be able to do what you want (if not, Mplus for sure). Hope this is helpful, Cam ---------------------------------------- > Date: Fri, 14 Aug 2009 13:27:15 -0700 > From: srmillis@yahoo.com > Subject: Re: st: Thinking through best way to do a longitudinal analysis > To: statalist@hsphsun2.harvard.edu > > Another option is to use a linear mixed model approach. > > Scott Millis > > > > > --- On Fri, 8/14/09, Polis, Chelsea B. wrote: > >> From: Polis, Chelsea B. >> Subject: st: Thinking through best way to do a longitudinal analysis >> To: "statalist@hsphsun2.harvard.edu" >> Date: Friday, August 14, 2009, 2:38 PM >> I am trying to do an analysis on the >> CD4 decline trajectory of 190 HIV+ women, comparing >> those who were on hormonal contraception around the time of >> HIV seroconversion against those >> who weren't. Each subject in my sample has at least >> two (and as many as six) CD4 measurements, >> the first and the last of which include a time span of at >> least one year. I created a >> variable to anchor the CD4 measurements in time by >> generating a variable that indicates how >> many days since HIV seroconversion the CD4 measurement was >> taken. The data are not balanced >> (since women have anywhere between 2 to 6 measurements) and >> CD4 counts were not measured for >> each individual at the same point in time after >> seroconversion (for example, the first measurement >> available for each woman ranges in days since >> seroconversion from 69 to 1919). >> >> I think one way to go about this would be to calculate the >> individual slope for each subject and >> compare the slopes between contraceptive users and >> non-users using a t-test. Is there a command >> to obtain those kind of individual regression slopes for >> each woman, and would my data have to be >> in long or wide format? >> >> Or am I thinking about this improperly? Would it be >> better to construct a longitudinal marginal >> model with generalized estimating equations, and if so, can >> someone point me in the direction of >> a text that might help me figure out how to do that with >> what I think is probably an unusual data >> structure (many of the examples I have seen in coursework >> use data measured at regular intervals)? >> >> Many thanks, >> Chelsea >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >> > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ _________________________________________________________________ Send and receive email from all of your webmail accounts. http://go.microsoft.com/?linkid=9671356 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Thinking through best way to do a longitudinal analysis***From:*"Polis, Chelsea B." <cpolis@jhsph.edu>

**Re: st: Thinking through best way to do a longitudinal analysis***From:*SR Millis <srmillis@yahoo.com>

**RE: st: Thinking through best way to do a longitudinal analysis***From:*Cameron McIntosh <cnm100@hotmail.com>

**RE: st: Thinking through best way to do a longitudinal analysis***From:*"Polis, Chelsea B." <cpolis@jhsph.edu>

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