Skip to content
Prev 177904 / 398502 Next

Gee with nested desgin

Dear Dimitris,

Thanks for your prompt reply.

I agree that the specification of the correlation structure in theory
only affects the efficiency. But I noticed that the fixed effects change
dramatically when comparing the unstructured correlation with my other
attempts. With most models the effect of Year is about -0.12. But with
the unstructured correlation structure it switches sign. So the effect
of Year becomes 0.10. In all models the effect of Year is strongly
significant.

Therefore I think I will stick to the model with PlotID as id and an
exchangeable correlation structure.

Regards,

Thierry


------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: Dimitris Rizopoulos [mailto:d.rizopoulos at erasmusmc.nl] 
Verzonden: woensdag 22 april 2009 11:48
Aan: ONKELINX, Thierry
CC: r-help at r-project.org
Onderwerp: Re: [R] Gee with nested desgin

Hi Thierry,

in geeglm() and in connection with the GEE theory, argument "id" should 
identify the independent sample units in your data set, which seem to be

the plots. GEE will produce consistent estimates even if you misspecify 
the correlation structure in your data (i.e., ignore nested design). If 
you specify it correctly, you gain in efficiency. So, in your case you 
may gain a little (or a lot) if you specify your own nested working 
correlation matrix. In geeglm(), argument 'corstr' gives the option for 
a user-defined correlation matrix, but I don't know how exactly this 
needs to be defined.

Regarding the 'waves' argument and AFAIK, this used in connection with 
the AR1 working correlation structure in order to identify the order and

spacing of the observations (i.e., if subject 1 has visits at time 1 and

time 2, whereas subject 2 has visits at time 1 and time 3).

A final thing: you said that you have some missing values. In this case 
note that the GEE approach will be valid (i.e., produce unbiased 
estimates) if the missing data mechanism is Missing Completely At 
Random, that is when the reasons for missingness do not depend on Y.

I hope it helps.

Best,
Dimitris
ONKELINX, Thierry wrote:
72.
missing,
unstructured
fixed
------------------------------------------------------------------------
more
to
not
schrijver weer
bevestigd is
message
as stating
by a duly
http://www.R-project.org/posting-guide.html