[R-sig-ME] longitudinal analysis using lmer?

[Ken Beath]

On 29/08/2009, at 6:07 AM, Robert Terwilliger wrote:

> One more thing........
>
> What i sent was only a small sample of the data, just for the purpose
> of showing what kind of set we have.
>
> We have about 150 subjects, with starting ages between 8 and 21, with
> 3-5 data points (yearly visits) per subject.
>

This will be fine, although it isn't as good as having a smaller  
number of complete series. One point is that they don't look  
completely linear, so a polynomial (maybe quadratic) or regression  
spline may be a better option. Judging by the scatter the random  
effect variance will probably be close to zero.

Ken




> Thanks,
>
> --
> Robert Terwilliger
> Physicist
> Laboratory of Neurocognitive Development
> Western Psychiatric Institute and Clinic
> University of Pittsburgh Medical Center
> Loeffler Building
> 121 Meyran Avenue  #114
> Pittsburgh, PA 15213
> 412.383.8174  - Office
> 412.383.8179 - Fax
> em: raterwil at gmail.com
> http://www.wpic.pitt.edu/research/lncd/
>
> *******************************************************
> Dear R mixed effects gurus,
>
> I have the following data below. Attached is a png graphic
> representing the data.
>
> I would like to run the following analysis:
>
> signal ~ age | subject.
>
> For your information (not statically relevant), the "signal" variable
> is from a functional MRI experiment.
>
> At issue is whether this analysis is valid using "lme". From the graph
> (and the table below), one can see that there are five subjects.
> However, each subject begins at a different age. Subject 1 begins at 8
> and goes to 12, while subject 5 begins at 14. From my study of
> longitudinal analysis, usually each subject begins at the same
> starting point, while these data have subjects beginning at different
> starting points (different ages).
>
> Any insight is appreciated.
>
> subject age     signal
> 1       8       0.108
> 1       9       0.139
> 1      10    NA
> 1       11      0.151
> 1       12      0.148
> 2       10      0.127
> 2      11    NA
> 2       12      0.135
> 2       13      0.146
> 3       9       0.105
> 3       10      0.123
> 3       11      0.134
> 3       12      0.151
> 3       13      0.145
> 4       12      0.130
> 4       13      0.169
> 4       14      0.146
> 4       15      0.174
> 5       14      0.158
> 5       15      0.141
> 5       16      0.178
> 5      17    NA
> 5       18      0.172
>
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