[R] Multivariable Wald to test equality of multinomial coefficients
prseye at gmail.com
Tue Oct 4 01:15:13 CEST 2016
I realise that and am not distilling it down to the p value. I am primarily considering the issue of collapsing down in the larger context of the added value/information that the extra categories give. However, I am curious to see (as I said from a statistical standpoint) whether the coefficients are sufficiently dissimilar.
On 4 October 2016 at 10:08:12 am, Bert Gunter (bgunter.4567 at gmail.com) wrote:
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Oct 3, 2016 at 3:30 PM, Paul Sanfilippo <prseye at gmail.com> wrote:
> I am trying to replicate a test in the Hosmer - Applied Logistic regression text (pp 289, 3rd ed) that uses a Multivariable Wald test to test the equality of coefficients across the 2 logits of a 3 category response multinomial model. I’d like to see whether (from a statistical standpoint) it is acceptable to collapse the 2 response categories and then simply use a binary logistic regression.
"The idea is that if the coefficients across the 2 logits are similar
(non-significant p value with Wald test), then it is reasonable to
pool the categories."
IMHO, this is a bad idea. See
Significance or lack of it is not a legitimate criterion on which to
base scientific decisions.
> There does not seem to be a built in way to do this in R?
> Using the mtcars dataset as an example (for the sake of the example, using cyl as a 3-factor response), does anyone have any ideas how to do this
> mtcars$cyl <- as.factor(mtcars$cyl)
> mtcars$am <- as.factor(mtcars$am)
> mod <- multinom(cyl ~ am + hp, data=mtcars)
> multinom(formula = cyl ~ am + hp, data = mtcars)
> (Intercept) am1 hp
> 6 -42.03847 -3.77398 0.4147498
> 8 -92.30944 -26.27554 0.7836576
> So, I want to simultaneously test whether the 3 coefficients across the 2 logits are similar.
> Thank you.
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