What your saying is true. The sequential/marginal difference can account for
the discrepancy in p values but not necessarily the coefficients. One thing
I've found that can lead to differences in coefficients and p values between R
and SPSS is whether or not you specify that a variable is a fa
Yes, but ... the original poster said the coefficients differed too.
(The blog post
you refer to deals with ANOVA (i.e. linear models) rather than GLMs (generalized
linear models): it is true that the sequential/marginal
distinction still applies, but I don't think that can be the *only*
thing
R usesType I sequential SS, not the default Type III marginal SS reported by
SPSS. There is a good blog post explaining this difference along with some
interesting comments --
http://myowelt.blogspot.com/2008/05/obtaining-same-anova-results-in-r-as-in.html
Best Wishes,
Martin H. Teicher
Dept
Leo Vorthoren nioo.knaw.nl> writes:
> I have been using generalized linear models in SPSS 18, in order to build
> models and to calculate the P values. When I was building models in Excel
> (using the intercept and Bs from SPSS), I noticed that the graphs differed
> from my expectations. When I r
I have been using generalized linear models in SPSS 18, in order to build
models and to calculate the P values. When I was building models in Excel
(using the intercept and Bs from SPSS), I noticed that the graphs differed
from my expectations. When I ran the dataset again in R, I got totally
diff
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