At 16:56 21/04/2008, Robert Junker wrote:
>Dear Statisticians,
>
>
>
>I would like to analyse my data with a GLM with binomial error distribution
>and logit link function. The point is that I want a model fitted without
>intercept, i.e. the fitted curve should start at y=0.5 for x=0.
>
>I tried it
On Tue, 2008-04-22 at 17:04 +0200, [EMAIL PROTECTED] wrote:
> Hi Robert,
>
> you can exclude the intercept by including "-1" in the formula:
>
> value <- as.numeric(runif(20)<.4)
> ppm <- rnorm(20)
> glm(value~ppm-1,family=binomial)
Note that 0+ppm is the same thing, try it:
glm(value ~ 0 + ppm
On Tue, 22 Apr 2008, [EMAIL PROTECTED] wrote:
> Hi Robert,
>
> you can exclude the intercept by including "-1" in the formula:
>
> value <- as.numeric(runif(20)<.4)
> ppm <- rnorm(20)
> glm(value~ppm-1,family=binomial)
Yes, but that is the same as 0 + ppm, which I tend to think is more
intuitive
Hi Robert,
you can exclude the intercept by including "-1" in the formula:
value <- as.numeric(runif(20)<.4)
ppm <- rnorm(20)
glm(value~ppm-1,family=binomial)
HTH
Stephan
> Dear Statisticians,
>
> I would like to analyse my data with a GLM with binomial error distribution
> and logit link fun
Dear Statisticians,
I would like to analyse my data with a GLM with binomial error distribution
and logit link function. The point is that I want a model fitted without
intercept, i.e. the fitted curve should start at y=0.5 for x=0.
I tried it with the following code:
glm(value~0+ppm, bi
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