[R-sig-ME] [Fwd: Errors in lme]

["Gerhard Göldner"]

Good day,

I am trying to do analysis on a dataset using mixed models because I have
samples from repeated individual animals.  Please find attached my
dataset.  The question I would like to pose is if and what are the effects
of the variable of distances and time on the proportional mass
change(propmc).  I have included other factorial effects such as age sex
and phase as well as year, but I don't know if I am using them correctly
in the model.

I have also attached the codes that I use for the model and the error
messages I am getting.  I have done some internet searches and some
suggest missing data as the culprit or fixed effects that are correlated.
Even if I exclude correlated fixed effects and only include fixed effects
which are not correlated with each other, I still get the same message
"error in MEEM - singularity in backsolve, level 0, block 1".

In addition, if I use for example a simpler model with only one fixed
effect, the model runs, but the output doesn't have p-values.. it only
says NaN.  I also did a search on that and found that it means Not a
number, though I don't know why it is producing that.  I noticed that the
DF is negative however and that if I use less variables, the DF increases
and the p value is calculated.  Is there a statistical way of using
t-values, without using p-values, as someone told me using AIC and
p-values are two different methodologies or philosophies.  In other words,
is it correct to still use the AIC values even if I don't get p-values and
just use the AIC values.

Can you please help me by making any suggestions about how to correct
this.  The "missing" data in my dataset are not missing - the values are
actually 0!

Thank you for any help you can give me - if not, could you please refer me
elsewhere?  I have your book "Mixed effects models in S and S-plus" 2000,
but would appreciate any help you can give me.

I would appreciate it very much.

Gerhard





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