random components of lme-model

Hi everyone,

I'm currently analysing a large dataset with measurements of nutrients in the Dutch marine systems in R. I have a variable "OffshoreDist" representing the distance from the sampling location to the coast. I also calculated the total amount of precipitation over The Netherlands and called this variable "Precip".What I want to do is link mean annual dissolved inorganic nitrogen (DIN) to the amount of precipitation. I expect that this relationship is dependent on the offshore distance. Distance classes can contain 1 or more sampling stations.

That's why I propose these two models with different random components:
model1 <- lme(log(DIN) ~ Precip:factor(OffshoreDist) + factor(OffshoreDist),
random= ~1station)
model2 <- lme(log(DIN) ~ Precip:factor(OffshoreDist) + factor(OffshoreDist),
random= ~Precipstation)

Are these the right models for random intercepts per station (model1) and random slope+intercept per station (model2)? Or should this be something like:

random = ~ factor(OffshoreDist) -1 station (model 1)
and
random = ~ Precip:factor(OffshoreDist)station (model 2)

I've read Pinheiro & Bates, 2000 which is a good reference, but explanation of the formulae only by means of examples does not seem to work for me.

Thanks in advance.

Cheers,

Tom Van Engeland

moved to new blogger

Hi,
I've moved the blog into the new google template. Everyone logging in will be invited to move her/his account too. A nice aspect of the change is that the blog can now be searched easily!
Cheers, Tom