>On Sat, 11 Jun 2005, John Fox wrote:
>
>>Dear Marc,
>>
>>I get the same results -- same coefficients, standard errors, and fitted
>>probabilities -- from multinom() and glm(). It's true that the deviances
>>differ, but they, I believe, are defined only up to an additive constant:
>
>Yes. There are
Dear Marc,
> -Original Message-
> From: Marc Girondot [mailto:[EMAIL PROTECTED]
> Sent: Saturday, June 11, 2005 2:16 PM
> To: John Fox
> Cc: [EMAIL PROTECTED]
> Subject: RE: [R] Problem with multinom ?
>
> >Dear Marc,
> >
> >I get the same result
>Dear Marc,
>
>I get the same results -- same coefficients, standard errors, and fitted
>probabilities -- from multinom() and glm(). It's true that the deviances
>differ, but they, I believe, are defined only up to an additive constant:
>
>> predict(dt.b, type="response")
> 1 2
>On Sat, 11 Jun 2005, John Fox wrote:
>
>>Dear Marc,
>>
>>I get the same results -- same coefficients, standard errors, and fitted
>>probabilities -- from multinom() and glm(). It's true that the deviances
>>differ, but they, I believe, are defined only up to an additive constant:
>
>Yes. There are
L PROTECTED] On Behalf Of Marc Girondot
Sent: Saturday, June 11, 2005 3:06 AM
To: John Fox
Cc: r-help@stat.math.ethz.ch
Subject: [R] Problem with multinom ?
Thanks for your response.
OK, multinom() is a more logical in this context.
But similar problem occurs:
Let these data to be analyzed using cl
--
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Marc Girondot
> Sent: Saturday, June 11, 2005 3:06 AM
> To: John Fox
> Cc: r-help@stat.math.ethz.ch
> Subject: [R] Problem with multinom ?
>
> Thanks for your response
Thanks for your response.
OK, multinom() is a more logical in this context.
But similar problem occurs:
Let these data to be analyzed using classical glm with binomial error:
m f factor m theo f theo
-Ln L model-Ln L full interecept
f
10 12 1.2 0.4524
