Hello,

I am using nlme to do a mixed effect repeated measures ANCOVA, with two
additional fixed factors  but a limited sample size. *I am seeking
clarification on how to/if I should adjust the inflated degrees of freedom
for a within-subject factor as a way of dealing with the temporal
pseudoreplication.

*More information: At 3 Sites on a river I measured fish Population in
approximately 9 stream Channel Units. Each Channel Unit was classified as a
Habitat, with three levels (Glide, Riffle, Pool). I sampled each Channel
Unit 3 times over the course of the summer, each time taking a Discharge
Measurement (thus the exact Discharge differs a little from Site to Site,
and so is a continuous variable). I want to know, does fish Population in
stream habitats (Glides, Riffles, Pools) change as discharge decreases over
the summer? Is there an interaction (I.e. Populations decrease in Riffles
with decreasing Discharge, but increase in Pools?). Is fish Population
different between habitats or between sites?

The model I have settled on to answer this question looks like this:
Pop.Model<-lme(Pop~Site+Habitat*Discharge, random=~1|ChannelUnit,
correlation=corCAR1(),data=mydata)

Inclusion of the three repeated measurements of Population in each Channel
Unit results in temporal pseudoreplication *and the degrees of freedom for
the within-subjects factor (Discharge) is 42, but I only have 26 Channel
Units, so this is obviously inflated (should be 21). I read in The R Book
(Crawley: *(Pg. 644,
https://www.dropbox.com/s/4zqewxl44btqmzo/Crawley%20The%20R%20book.pdf*)
that I can fix this by specifying  the degrees of freedom. But how?*
*
Although I’ve read a ton online, including Bates info re: SAS vs R and
degrees of freedom I find that I am still quite confused. If anyone can
offer specific advice on how I can adjust my degrees of freedom for the
within-subjects factor or explain in accessible terms why I don’t need to,
I would be very grateful. *

Just in case I haven't provided enough information, here is my data and r
code.
.csv file:
https://www.dropbox.com/s/2ijgq74di3hmo8i/R.Help.csv
.R file:
https://www.dropbox.com/s/puj5maifxc2rfcg/R%20Help.R
.doc with code & diagram:
https://www.dropbox.com/s/29dtofc62t957co/R%20Help.doc

Sincerely,

Stephanie Avery-Gomm
MSc. Candidate, Zoology Department
University of British Columbia


-- 
-- 
Stephanie Avery-Gomm
Master's Candidate
Zoology Department,
University of British Columbia
#4200-6270 University Blvd.
Vancouver, B.C. V6T 1Z4
Email: Stephanie.AveryGomm@gmail.com
 Cell: 778 322 3483
Web: http://ca.linkedin.com/in/stephanieaverygomm

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