Dear All,
I am using the function gls (in the nlme package) and I would like to fit a
heteroscedastic model, with different variances for each of the levels of two
stratification variables.
In p. 210 of Pinheiro & Bates ("Mixed effects models in S and
S-Plus", 2000,
Springer), the authors show the use of the "*" operator. However, that
is not
what I want, because it fits a different variance parameter to each
combination of the two levels. What I would like is more along the ways of p.
163 and ff., where they fit models with crossed random effects.
I think this can be achieved using varComb. If we have two strata, say ID1 and
ID2, we can do:
gls(my.formula,
weights = varComb( varIdent(form = ~ 1 | ID), varIdent(form = ~ 1 | ID2)))
This seems to work (and to produce reasonable results) but I am not sure if it
is right, or I am doing something dumb.
Best,
--
Ram?n D?az-Uriarte
Bioinformatics Unit
Centro Nacional de Investigaciones Oncol?gicas (CNIO)
(Spanish National Cancer Center)
Melchor Fern?ndez Almagro, 3
28029 Madrid (Spain)
http://bioinfo.cnio.es/~rdiaz
