Hi Thierry,

You're very right and I was very wrong. It's a warning indeed, and the
outcome is close to what I become if I calculate the logit transformation
myself (although not exactly the same, but I guess that has to do with the
correction the logit function does when p=0 or p=1).

I should have paid more attention to the course of categorical ;-)
Kind regards
Joris

On Wed, Mar 25, 2009 at 10:32 AM, ONKELINX, Thierry <
Thierry.ONKELINX@inbo.be> wrote:

> Hi Joris,
>
> glm() handles proportions but will give you a warning (and not an error)
> about non-integer values. So if you get an error then there should be
> something wrong with the syntax, model or data. Can you provide us with
> a reproducible example?
>
> Cheers,
>
> Thierry
>
>
> ------------------------------------------------------------------------
> ----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature
> and Forest
> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
> methodology and quality assurance
> Gaverstraat 4
> 9500 Geraardsbergen
> Belgium
> tel. + 32 54/436 185
> Thierry.Onkelinx@inbo.be
> www.inbo.be
>
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to
> say what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> 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
>
> -----Oorspronkelijk bericht-----
> Van: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org]
> Namens joris meys
> Verzonden: dinsdag 24 maart 2009 20:30
> Aan: R-help Mailing List
> Onderwerp: [R] modelling probabilities instead of binary data with
> logisticregression
>
> Dear all,
>
> I have a dataset where I reduced the dimensionality, and now I have a
> response variable with probabilities/proportions between 0 and 1. I
> wanted
> to do a logistic regression on those, but the function glm refuses to do
> that with non-integer values in the response. I also tried lrm, but that
> one
> interpretes the probabilities as different levels and gives for every
> level
> a different intercept. Not exactly what I want...
>
> Is there a way to specify that the response variable should be
> interpreted
> as a probability?
>
> Kind regards
> Joris
>
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