[R-sig-ME] Advice on GLMM with verIdent

Diego Pavon diego.pavonjordan at gmail.com
Tue Dec 20 17:49:46 CET 2016

Dear all,

I write you because I need some advice about the model I want to fit to my
data, which I suspect it is not too 'correct'...

My response variable is continuous (mean weighted latitude) of 24 species.
I have these mean latitudes calculated for 4 periods (95-99, 00-04, 05-09,
10-13), for each species. Therefore I have 96 observations. I want to see
if there is a trend of the mean latitude over time (indicating a shift in
the population... all the species together). In this case, I would use
Period as a continuous varaible and not a factor. I want to fit a GLMM with
random = SpeciesID. However, data exploration revealed a quadratic
relationship between my response (mean latitude) and Period (my continuous
covariate for time). But also, I am interested also to see whether there
are differences between functional groups (some species may move faster
than others). Thus I include the variable Phylogeny, which is a factor with
5 levels. Thus, the model in nlme notation is:

lme(NEnessKM ~ Period_std + I(Period_std^2) + factor(Phylogeny)
          + Period_std : factor(Phylogeny) + I(Period_std^2) :
          random = ~1| factor(Species),
          weights = varIdent(form =~ 1 | factor(Species)),
          control = ctrl2,
          method = "REML",
          data = NEness5y)

My concern is that this model might be too complicated. I have only 96
observation. If I follow the rule of 15 observation per parameter
estimated, this model i way to complex. I understand that in order to
include quadratic terms, one must include also the linear effect... and
that would also apply for the interactions. If the relationship between my
response (NEness = Mean Latitude) and Period is a parabola, I guess I
should include also the Period^2 in the interaction (Period^2 * Phylogeny)?
But in that case, I have to include the interaction of Period * Phylogany?

Is there a way to reduce the complexity? Is it totally wrong if I do not
include the linear effects and keep only Period^2?

Thanks for sharing your knowledge and for the advice.



*Diego Pavón Jordán*

*Finnish Museum of Natural History*
*PO BOX 17 *

*Helsinki. Finland*


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