[R] different outcomes of P values in SPSS and R

in SPSS and glm(formula = EPO_YN ~ frequ_ind + frequ_ind2 + frequ_preFDS, family = binomial(link = logit), data = w) in R. -- View this message in context: http://r.789695.n4.nabble.com/different-outcomes-of-P-values-in-SPSS-and-R-tp2324181p2324181.html Sent from the R help mailing list archive

Re: [R] different outcomes of P values in SPSS and R

Leo Vorthoren L.Vorthoren at 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

Re: [R] different outcomes of P values in SPSS and R

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

Re: [R] different outcomes of P values in SPSS and R

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

Re: [R] different outcomes of P values in SPSS and R

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