Hi, I am new to this list as a poster, but a reader for some time. I've using R for several weeks now, and I have a lot of questions about certain procedures. Here I go: I want to test if there are differences in the time spent by pollinators visiting flowers of a given plant species, according to a number of experimental manipulations made on those flowers. All experimental manipulations (factor with 5 levels) are replicated within plants (i.e. plant is my sampling unit). Further, I have two populations (two level factor), and a number of pollinator groups (again, two levels, the same in both populations). The response variables in the numbe of seconds invested in each probe. Further, I have plant floral display as a covariate, as it may influence visitation rates. I think I have to analyse this desing considering population, pollinator group and their interaction as fixed effects, and treatment nested within plant, and its interaction with population and pollinator group, as random factors. In SAS terminology, the model looks like this: proc mixed data=flwfunc.visitflower covtest method=reml; class site pollclass treatm plantid; model time = site|pollclass flwinflor / chisq; random treatm site*treatm pollclass*treatm / subject=plantid; lsmeans site pollclass site*pollclass; run; I've been successfully trying lm, but I think is not suitable for random effects. Thus, I've tried lme, but no success when defining the random part or trying to interpret the results... Any help will be welcome! -- ---------------------------------------------- Alfonso M. Sanchez-Lafuente Departamento de Biologia Vegetal y Ecologia Facultad de Biologia Universidad de Sevilla Avd. Reina Mercedes 9 E-41012, Sevilla, Spain email: alfonso at slafuente.net / slafuente at us.es
Hi,
I am new to this list as a poster, but a reader for some time.
I've using R for several weeks now, and I have a lot of questions about
certain procedures. Here I go:
I want to test if there are differences in the time spent by pollinators
visiting flowers of a given plant species, according to a number of
experimental manipulations made on those flowers. All experimental
manipulations (factor with 5 levels) are replicated within plants (i.e.
plant is my sampling unit). Further, I have two populations (two level
factor), and a number of pollinator groups (again, two levels, the same
in both populations). The response variables in the numbe of seconds
invested in each probe. Further, I have plant floral display as a
covariate, as it may influence visitation rates.
I think I have to analyse this desing considering population, pollinator
group and their interaction as fixed effects, and treatment nested
within plant, and its interaction with population and pollinator group,
as random factors.
In SAS terminology, the model looks like this:
proc mixed data=flwfunc.visitflower covtest method=reml;
class site pollclass treatm plantid;
model time = site|pollclass flwinflor / chisq;
random treatm site*treatm pollclass*treatm / subject=plantid;
lsmeans site pollclass site*pollclass;
run;
I've been successfully trying lm, but I think is not suitable for random
effects. Thus, I've tried lme, but no success when defining the random
part or trying to interpret the results...
Any help will be welcome!
--
----------------------------------------------
Alfonso M. Sanchez-Lafuente
Departamento de Biologia Vegetal y Ecologia
Facultad de Biologia
Universidad de Sevilla
Avd. Reina Mercedes 9
E-41012, Sevilla, Spain
email: alfonso at slafuente.net / slafuente at us.es