[R-sig-ME] GLMMpql and GEE question

[Hannah L. Linder]

Hi,

I am an M.S. student at the University of Washington School of Aquatic and
Fishery Sciences.My thesis involves the comparison of many models that you
could use to analyze monitoring data. A big part of this comparison is
looking at models with and without autocorrelation (my data is a univariate
time series). I was hoping to compare a GLS, GLM, and GLM with
autocorrelation for a non-normal data set using their RMSE values. I was
originally intending to use a GLM-GEE, because I have seen them used in the
literature within my field, but I noticed the glmmPQL function allows for
different corARMA correlation structure and the gee only allow for an ar-1
correlation structure. So now, I believe that I would rather use the
glmmPQL for the purpose of comparing a model that allows for
autocorrelation but is normally distributed (GLS), one that is non-normal
with no autocorrelation (GLM), and one that is non-normal with
autocorrelation. I am wondering if there is a big difference between the
glmmPQL model and a glm-gee? I know the gee is a marginal model, and a glmm
models random effects, but in the case of a univariate time series (which
is essentially a single group) I am not sure how this would make a big
difference.


If anyone has any time to provide suggestions on better understanding the
difference between these two models, or if it is appropriate to use a glmm
rather than a gee in this case, I would greatly appreciate it.

Thank-you very much,
Hannah Linder

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