[R-sig-eco] Proper treatment of Proportion Response Data with Two Categorical Predictors

[Aitor Gastón]

Everett,

If you have the original binary data that were used to calculate proportions 
you can use generalized linear models with logit link (i.e. logistic 
regression). You can find a simple explanation of this approach and some 
examples with R code in 
http://www.bio.ic.ac.uk/research/crawley/statistics/exercises/R10Proportiondata.pdf

Aitor


--------------------------------------------------
From: "Everett" <ehanna23 at uwo.ca>
Sent: Tuesday, December 11, 2012 12:19 AM
To: <r-sig-ecology at r-project.org>
Subject: [R-sig-eco] Proper treatment of Proportion Response Data with Two 
Categorical Predictors

> Hello,
>
> I believe I have exhausted my online resources (and eyes) in trying to
> determine the appropriate method of analysis for the following
> investigation.
>
> I wish to determine if the efficiencies (% recovery) of two sampling units
> are significantly different. I sampled in three different fields. I
> attempted to collect 12 samples per unit per field (2 x 12 x 3 = 72);
> however, some sample sites had no seeds and resulting data were excluded 
> (so
> as to not confuse with 'true' zero data; i.e., 0 seeds of x recovered).
> Working sample size = 24 and 27 (51), per unit.
>
> My dataset sets up like this:
>
> 1) 51 observations
> 2) Response variable = percent seeds recovered; x = 0-1
> 3) Predictor variable 1 = unit (K or L); fixed categorical
> 4) Predictor variable 2 = field (1, 2, or 3); random categorical
>
> More than 50% of my data are zeros, therefore, the distribution is far 
> from
> normal.
>
> Can someone provide guidance RE how best to proceed? Thank you kindly in
> advance.
>
> -Everett
>
>
>
>
> --
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