[R] GAM-binomial logit link

[Monica Pisica]

Hi,

I am not sure it is the best to use a binomial distribution for a continuous bounded variable. A beta distribution would be more appropriate, although I don't know how to define one for the gam() function. On the other hand beta distribution is closely linked to the gamma distribution so maybe you can use it to define a beta family for the gam() function.

Some info about beta distribution: http://www.stat.purdue.edu/~jrnolan/portfolio/the_big_ten/beta.pdf

Also, I am not very sure how you did a gam using binomial family without having your response data converted in 0 and 1. Didn't you get a warning saying that:
Warning messages:
1: In eval(expr, envir, enclos) ... : non-integer #successes in a binomial glm!

Maybe you can contact the author of the mgcv package. I am curious to see his response.

Sorry I cannot help much more,

Monica

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Message: 96
Date: Thu, 21 Aug 2008 00:53:52 +0200
From: Marina Laborde 
Subject: [R] GAM-binomial logit link
To: 
Message-ID: 
Content-Type: text/plain


Dear all,

I'm using a binomial distribution with a logit link function to fit a GAM model. I have 2 questions about it.
First i am not sure if i've chosen the most adequate distribution. I don't have presence/absence data (0/1) but I do have a rate which values vary between 0 and 1. This means the response variable is continuous even if within a limited interval. Should i use binomial?
Secondly, in the numerical output i get negative values of UBRE score. I would like to know if one should consider the lowest absolute value or the lowest real value to select the best model.

Thank you in advance for your help.
Marina


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