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 ?
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]
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) ~
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(
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
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