[R] modeling binary response variables

[Daniel Malter]

thanks


Simon Blomberg-4 wrote:
> 
> 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
> 
> Policies:
> 1.  I will NOT analyse your data for you.
> 2.  Your deadline is your problem.
> 
> The combination of some data and an aching desire for 
> an answer does not ensure that a reasonable answer can 
> be extracted from a given body of data. - John Tukey.
> 
> ______________________________________________
> 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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