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 Mal
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 be
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 c
Wait, are the proportions (probabilities) based on discrete data, or are
they truly continuous? If the latter, then beta regression might be more
appropriate (e.g. package betareg). If the former, include the sample
size for each proportion in the call to glm using the weights= argument.
Or set the
Hi Kevin, you mean an s-shaped relationship of a variable with your response?
So you have a response that is strictly constrained to the interval 0,1 or,
and these limits are not due to truncation or censoring (i.e. your response
variable is truly a proportion).
This sounds like a good applicatio
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
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