Re: [R] Genmod in SAS vs. glm in R

2008-09-10 Thread Tobias Verbeke
Ajay ohri wrote: Whats the R equivalent for Proc logistic in SAS ? glm with the appropriate family (binomial) and link, I guess. There is a book 'R for SAS and SPSS users' forthcoming http://www.springer.com/statistics/computational/book/978-0-387-09417-5 Is there a stepwise method there ?

Re: [R] Genmod in SAS vs. glm in R

2008-09-10 Thread Ajay ohri
Whats the R equivalent for Proc logistic in SAS ? Is there a stepwise method there ? How to create scoring models in R , for larger datasets (200 mb), Is there a way to compress and use datasets (like options compress=yes;) Ajay On Wed, Sep 10, 2008 at 11:12 AM, Peter Dalgaard <[EMAIL PROTECTED]

Re: [R] Genmod in SAS vs. glm in R

2008-09-09 Thread Peter Dalgaard
Rolf Turner wrote: For one thing your call to glm() is wrong --- didn't you notice the warning messages about ``non-integer #successes in a binomial glm!''? You need to do either: glm(r/k ~ x, family=binomial(link='cloglog'), data=bin_data, offset=log(y), weights=k) or: glm(cbind(r,k-r) ~

Re: [R] Genmod in SAS vs. glm in R

2008-09-09 Thread Rolf Turner
For one thing your call to glm() is wrong --- didn't you notice the warning messages about ``non-integer #successes in a binomial glm!''? You need to do either: glm(r/k ~ x, family=binomial(link='cloglog'), data=bin_data, offset=log(y), weights=k) or: glm(cbind(r,k-r) ~ x, family=binomial(

[R] Genmod in SAS vs. glm in R

2008-09-09 Thread sandsky
Hello, I have different results from these two softwares for a simple binomial GLM problem. >From Genmod in SAS: LogLikelihood=-4.75, coeff(intercept)=-3.59, coeff(x)=0.95 >From glm in R: LogLikelihood=-0.94, coeff(intercept)=-3.99, coeff(x)=1.36 Is there anyone tell me what I did wrong? Here