[R] modeling binary response variables

[Simon Blomberg]

Jim Lindsey's repeated package has the function gnlmm which will fit
beta regressions with a random intercept and one level of nesting. I
don't know of any other options.

Cheers,

Simon.

 Not sure On Mon, 2008-07-14 at 19:16 -0700, Daniel Malter wrote:
> 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
> > 
> > ______________________________________________
> > 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.
> > 
> > 
> 
-- 
Simon Blomberg, BSc (Hons), PhD, MAppStat. 
Lecturer and Consultant Statistician 
Faculty of Biological and Chemical Sciences 
The University of Queensland 
St. Lucia Queensland 4072 
Australia
Room 320 Goddard Building (8)
T: +61 7 3365 2506
http://www.uq.edu.au/~uqsblomb
email: S.Blomberg1_at_uq.edu.au

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