[R] Hierarchical glm
Pascal A. Niklaus
Pascal.Niklaus at unibas.ch
Thu Nov 6 17:48:52 CET 2003
Hi all,
I'm not sure how to correctly analyse the following data with glm, and
hope for some advice from this list, ideally showing how to specify the
model in R and perform the tests, and also for suggestions of literature.
The data structure is like this:
- 20 plant populations were investigated (random factor pop), which
belong to different habitat types (factor ht)
- Within each plant population, individuals were grouped into 3 size
classes (factor sz)
- For each individual, some count data were recorded
The independent variables I'd like to analyse are either poission of
binomially distributed.
For gaussian data, I would use the following model:
ht + pop %in% ht + sz + sz:ht + sz : pop %in %ht
ht would basically be tested against pop (because the population is the
unit of replication for ht), and sz against sz:pop:ht. (the hypotheses
to test are that ht has an effect, and whether the effect of sz on
individuals of a population depends on ht)
However, I do not know how to translate this to the deviance analysis
case. For example, when I fit the whole model, and then drop ht to test
for the effect of ht, the effect of ht shows up in pop (I understand
why, but don't know how to do this otherwise). If I compare the null
model to the model including ht only, do I then commit a pseudoreplication?
Thanks for your help
Pascal
More information about the R-help
mailing list