I'm assuming you're trying to interpret the results of a logistic
regression. If something else is your goal, please let us know.

Here's a starting page you can try:
http://www.ats.ucla.edu/stat/mult_pkg/faq/general/odds_ratio.htm
In short, logistic regression gives you the odds of something happening
against something not happening. So one level is XX times more/less likely
to happen than the other.
I also suggest you read up on validating your logistic model (like ROC plot
besides the standard checking of residuals).

Cheers,
Roman


On Sat, Jul 20, 2013 at 5:00 AM, Moshiur Rahman <mrahmankufmrt@gmail.com>wrote:

> Dear R-helpers,
>
> I did an experiment with Guppy where I had two dietary groups ("High" and
> "Low"). I completed all my data analysis, but stacked in "paternity
> analysis". I ran the attached model to analyse them, but as a novice in R,
> it's very hard for me to confirm whether this gives me the correct output
> or not. I would like to examine the effect of the predictor traits (VAP,
> Viability, Body FAs) on paternity success (Proportion). Here, I fitted
> generalized linear models (GLMs) using a logit-link function as my data has
> some zeroes and ones. I also like to use quasi-GLMs to correct for
> overdispersion. Now, I need some help from you guys to estimate the
> paternity success of my high group or both groups?
>
>  With kind regards,
>
>
> On Sat, Jul 20, 2013 at 10:51 AM, <r-sig-ecology-request@r-project.org
> >wrote:
>
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> --
> MD. MOSHIUR RAHMAN
> PhD Candidate
> School of Animal Biology/Zoology (M092)
> University of Western Australia
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> Australia.
> Mob.: 061-425205507
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-- 
In God we trust, all others bring data.

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