Degrees of freedom in multinomial regression

[TorB]

Hi,

I am running multinomial regression on:

4 categorical predictors (responses to 4 questions) - (each of the 4 questions can be answered by one of 5 categories)
1 outcome/dependent variable, which is a rating score (with 5 categories)


To see if respondents responses to each of the 4 questions can be used to predict the rating score.

There are no covariates.

I am struggling to understand how the df in the likelihood ration tests are calculated - this = 64, and then in the Pearson and Deviance tests = 32.

Can anyone assist, or advise where I could find a clear explanation?

Many thanks

VB

[Rich Ulrich]

Having 4 questions (categories 1-5) give you 16 degrees of freedom for predicting,
when you treat them as categories.

Having 5 categories of Outcome gives you 4 equations - each with 16 d.f.

There's your 64 d.f.  for the likelihood test.

The example that I Googled up doesn't show the Pearson/Deviance tests,
but maybe this is enough clue.

--
Rich Ulrich

> Date: Sun, 13 Apr 2014 09:35:49 -0700

> From: [hidden email]
> Subject: Degrees of freedom in multinomial regression
> To: [hidden email]
>
> Hi,
>
> I am running multinomial regression on:
>
> 4 categorical predictors (responses to 4 questions) - (each of the 4
> questions can be answered by one of 5 categories)
> 1 outcome/dependent variable, which is a rating score (with 5 categories)
>
>
> To see if respondents responses to each of the 4 questions can be used to
> predict the rating score.
>
> There are no covariates.
>
> I am struggling to understand how the df in the likelihood ration tests are
> calculated - this = 64, and then in the Pearson and Deviance tests = 32.
>
> Can anyone assist, or advise where I could find a clear explanation?
>
> Many thanks
>
> VB
>

[Art Kendall]

It is important to know exactly what values each of the variables can take, and what the meaning is of each IV and DV before list members can comment on your problem.
On 4/13/2014 12:35 PM, TorB [via SPSSX Discussion] wrote:

Hi,

I am running multinomial regression on:

4 categorical predictors (responses to 4 questions) - (each of the 4 questions can be answered by one of 5 categories)
1 outcome/dependent variable, which is a rating score (with 5 categories)


To see if respondents responses to each of the 4 questions can be used to predict the rating score.

There are no covariates.

I am struggling to understand how the df in the likelihood ration tests are calculated - this = 64, and then in the Pearson and Deviance tests = 32.

Can anyone assist, or advise where I could find a clear explanation?

Many thanks

VB

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