Re: [R] modeling binary response variables

From: Daniel Malter <daniel_at_umd.edu>
Date: Mon, 14 Jul 2008 19:16:57 -0700 (PDT)

I have a connector-question to that. Is beta-regression available for repeated measures or panel data and if so is it available in R?

thx,
Daniel

Kevin J Emerson wrote:
>
> R-devotees,
>
> I have a question about modeling in the case where the response variable
> is
> binary.
>
> I have a case where I have a response variable that is the probability of
> success, and four descriptor variables, The response has a sigmoid
> response
> with one of the variables. I would like to test for the effect of the
> various descriptor variables on the percentage success of the binary
> trait.
> I have looked at glm with family = "binomial" but am not sure I totally
> understand its use (and therefore am not sure it is the appropriate test)
> and am looking for two things: (1) is glm with family = 'binomial' the
> right
> way to do this, and (2) are there any good references on how it works.
> I have posted a plot of a sample of the data I am looking at as well as
> the
> sample data used to generate the plots.
>
> Sample Plot: http://www.uoregon.edu/~kemerson/tmp/plot.pdf
> Sample Data: http://www.uoregon.edu/~kemerson/tmp/data.csv
>
> Response variable is percent.dev (se2.dev are the errors from binomial
> estimates given probability and number of samples).
>
> Descriptor variables are num.days, ppd, temp, and pop.
>
> Any help would be greatly appreciated.
>
> Cheers,
> Kevin Emerson
>
>
> ====================================
> Kevin J. Emerson
> Bradshaw - Holzapfel Lab
> 1210 University of Oregon
> Eugene, OR, 97403
> email: kemerson_at_uoregon.edu
> web: http://evodevo.uoregon.edu/people/emerson.html
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>

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Received on Tue 15 Jul 2008 - 02:20:16 GMT

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