[R] modeling binary response variables

[Kevin J Emerson]

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