Re: unbalanced repeated measures

Dear ASRemlers,

After having posted a question of how to best analyze my longitudinal
data with missing values, Arthur suggested I should use a random
regression approach with fitting cubic splines to the longitudinal data
of individuals. The working code is below.
The result suggests that age at measurement (=callage) is not
significant, but size of the animal (=size) is highly significant.
In order to fully understand this, I tried to visualize it, but when I
plot eg. the residuals out of the model without size, against size, I
can't see any sort of pattern.

My first question is whether I'm missing something fundamentally.
I'm also not quite sure whether I need to fit cubic splines, as my
ultimate question is only to see whether my dv (=call) shows a decrease
with increasing age.

As before, I'm thankful for any comments,

Cheers,
Felix

Working code (measured variable is call=calling effort, at 13 ages
(callage) throughout an individuals life):
Random regression analysis
         ind !I
         eclosed
         size
         temp
         callage
         call
males-readyFORasremlreduced.txt !SKIP1 !DISPLAY 9 !MAXIT 200
call !POISSON !DISP ~ mu callage size !r spl(callage) fac(callage) ind
callage.ind !f mv
1 2 1
81
13 0 AR1 0.1 !GP
ind 2
ind
2 0 US !GP
.1 0.01 .1
ind

______________________________________________________________
::Felix Zajitschek
::School of Biological, Earth and Environmental Sciences (BEES)
::University of New South Wales (UNSW) NSW 2052 - Australia
::Labtel +61 (0)2 9385 2124
::Fax +61 (0)2 9385 1558
::eMail <mailto:felix.zajitschek_at_student.unsw.edu.au>
felix.zajitschek_at_student.unsw.edu.au
::
<http://www.bees.unsw.edu.au/school/researchstudents/zajitschekfelix.htm
l> www.bees.unsw.edu.au/school/researchstudents/zajitschekfelix.html
:: <http://evoecosexunsw.blogspot.com/> Lab Blog
Received on Wed Oct 27 2006 - 16:23:56 EST