On 21/07/14 19:52, Samantha PameLa wrote:
Good day everybody,
I'm a marine biologist student, working on my bachelor thesis and I'm stucked with a statistical doubt in the process, I hope someone here could help me. My thesis aims to understand which biological and environmental factors influences the male aggressive rate of male California sea lions. For that purpose I'm using GLM’s where the response variable is the male aggressive rate. Right now I am testing the goodness of fit of the global models and for that I'm using the deviances as a goodness of fit test. I calculated pseudoR2 (Zuur, 2009) in order to know the percentage of explanation of each candidate model. However I’m not sure how to choose the “good models”; since I am not sure over which percent of explanation indicates a “model with good fit”. For my data I am working with three different scenarios, and it seems that 20%, is a good value to could indicate the best models, but I’m not sure how to choose the value.
I thank you in advance for your time and the help you can give me.
Best regards,
Just to follow up, AIC isn't a measure of model fit either: it's a
measure of model adequacy, and can be used to compare different models.
For model fit, you can (usually) compare the residual deviance to the
degrees of freedom (they should be approximately equal, and you can use
a chi-squared test, if you feel the need to generate a p-value). This
doesn't work if your response is binomial with a small N (and psuedo R2
doesn't work terribly well for this case either).
A better approach to checking if the model fits is to check to see if
the residuals have any gross patterns in them, by plotting them against
the fitted values and also against covariates.
If you'll excuse my self-promotion, PNAS recently gave me an excuse to
show some residual plots to the general public:
<http://www.theguardian.com/science/grrlscientist/2014/jun/04/hurricane-gender-name-bias-sexism-statistics>
(my explanation for why this is not just gratuitous self-promotion is
that I linked to the R code to generate the plots too, so you have
something to work from).
Bob
--
Bob O'Hara
Biodiversity and Climate Research Centre
Senckenberganlage 25
D-60325 Frankfurt am Main,
Germany
Tel: +49 69 7542 1863
Mobile: +49 1515 888 5440
WWW: http://www.bik-f.de/root/index.php?page_id=219
Blog: http://blogs.nature.com/boboh
Journal of Negative Results - EEB: www.jnr-eeb.org
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