From: Daniel Malter <daniel_at_umd.edu>

Date: Mon, 14 Jul 2008 18:07:15 -0700 (PDT)

Date: Mon, 14 Jul 2008 18:07:15 -0700 (PDT)

Then you can run the binomial as follows:

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
**>
**> ______________________________________________
**> R-help_at_r-project.org mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> 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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