Malcolm,
Have a look at the package 'unmarked' for a direct implementation of
some flavors of OMs in R.
http://cran.r-project.org/web/packages/unmarked
Also look at package 'RMark' for constructing OMs for fitting in
program MARK (results returned to R as objects). RMark is available
here:
http:/
What answers have you found and why were they unsatisfactory?
First, use AICc, not AIC. See Burnham and Anderson 2002 or Anderson
2008 (Primer).
Second, I think most all literature is rather clear that models with
deltaAICc < 2 are basically equivalent. So of course you should report
support for
Hilit,
You don't have to be a whiz to use LaTeX, especially not now with LyX:
www.lyx.org
One of its greatest advantages for me is the reference handling
(combined with JabRef). Give 'em a try, and save yourself a pile of $
in the process.
- Dave Hewitt
From: Hilit Finkler
Subject: mac/end
Short answer: No. You probably don't have enough data to estimate what you
want to estimate.
Long answer: You didn't provide enough information for anyone to help you.
Do some searching on the forum dedicated to such modeling in MARK at
http://www.phidot.org/forum and then follow up with folks the
Hi Andrew,
My message was predicated on the poster (Howie) treating his analysis
using ANCOVA in its simplest typical form, a single-factor covariance
model. The "full" model is the one you give as #3.
A start of an answer to your first question would be that the ANOVA
table for this "full" model
I certainly agree with Gareth that the ANCOVA approach should be
simple. But it won't address all hypotheses posed by the "slopes
and/or intercepts" framework. What you need is a model selection
approach. Fit the various linear models of interest (some of which may
be ANCOVA-type models), calculate
> Date: Mon, 8 Feb 2010 13:57:54 -0500
> From: Bruce Robertson
> Subject: AIC, data-dredging, and inappropriate stats
>
> Dear Ecologists,
>
> I've been using an information-theoretic model-selection approach as a
> part of my research and have found that the ecological literature
> appears
Isabelle,
I don't think any statistical method will do you much good if you only
have four subjects.
If you have a larger sample size such that some general inference
about a treatment effect is reasonable, here's two references worth
checking out:
Gelman and Hill. 2007. Data analysis using regr
anced data.
R http://www.r-project.org/
See Documentation -> Manuals to get started on setting up the
model(s), including the many excellent contributed documentation
sources.
----------
David Hewitt
Research Fishery Biologist
USGS Western Fisheries Research Ce
