> Host (fixed) > Sire (random) > Dam nested within Sire (random) > Host * Sire (random) > Host * Dam within Sire (random) > > So without the interactions I have: > > hogmodel = lme(gain ~ host, random = ~1|sire/dam) > > If I understand correctly, that "sire/dam" term gives me both > Sire and Dam within Sire as random factors. OK, so now I want > to add the two interactions (listed above)...
Correct, for the interactions write: random = ~ host | sire/dam an interaction between a fixed and a random term can be interpreted as a variability in the fixed term for the different levels in the random term. Thus the 1 (which stands for the intercept) is exchanged with the fixed effect(s) with which interactions are of interest. This is easy if all the hierarchical levels of a nested random effects go into an interaction it is a bit more complicated if not. Say you only want the interaction of host and dam but not sire: random = list (~ 1 | sire, ~ host | dam) Hope this helps (it can all be found in Pinheiro and Bates and on the help pages). Lorenz ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
