This is R-help, not a list that provides statistical help (primarily;
they do intersect at times). Post to the r-sig-mixed-models list
instead. You're likely to do better there anyway for this sort of
thing.
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
H. Gilbert Welch
On Thu, Apr 3, 2014 at 6:29 AM, Nick Negovetich <nj.negovet...@gmail.com> wrote:
> Greetings,
>
> I have a question regarding data analysis of habitat use of animals. These
> animals were radio collared and tracked periodically throughout the year.
> When they were sighted/detected, the habitat type was marked. Our dataset
> recorded the sex of the animal, and we know the data when the surveys were
> performed. The goal was to address the questions: does habitat use differ
> between the sexes, and does habitat use vary between seasons? Below is a
> summary table, ignoring seasons.
>
> dattab <- matrix(c(190,87,206,170,103,23,66,72,53,22),nrow=5,byrow=T)
> rownames(dattab) <- c("Rock","Burrow","Cactus","Brushpile","Other")
> colnames(dattab) <- c("Female","Male")
> dattab
> Female Male
> Rock 190 87
> Burrow 206 170
> Cactus 103 23
> Brushpile 66 72
> Other 53 22
>
> We could perform a test of independence, but the problem lies with our
> assumptions. Because individual animals were tracked through time, each
> animal give a different number of datapoints (min=1, max=126), which
> violates our assumption of independence. Thus, our sampling unit should be
> at the level of the skunk and analysis should proceed from there. I'm
> familiar (theory and practice) with linear mixed effect models, but I
> believe that these data call for a mixed effects MANOVA. Is there such a
> test in R? Or, would it be better to analyze the data using a standard
> MANOVA where our y1, y2, ... are the percentage of data points within that
> various habitats? My problem with this last analysis is that each skunk will
> carry the same weight even though both could have a large difference in the
> number of data points. Thanks...
>
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