[R] Checking the assumptions for a proper GLM model
dwinsemius at comcast.net
Thu Feb 18 18:01:56 CET 2010
At one time the "answer" would have been to buy a copy of Venables and
Ripley's "Modern Applied Statistics with S" (and R), and that would
still be a sensible strategy. There are now quite a few other R-
centric texts that have been published in the last few years. Search
Amazon if needed. You seem to be asking for a tutorial on general
linear modeling (which if you read the Posting Guide you will find is
not a service offered by the r-help list.) Perhaps you should have
edited the link you provided in the obvious fashion:
Perhaps one of these pages:
The UCLA Statistics website used to be dismissive of R, but they more
recently appear to have seen the light. There is also a great amount
of contributed teaching material on CRAN:
... and more would be readily available via Googling with "r-project"
as part of a search strategy. Frank Harrell's material is in
particular quite useful:
On Feb 18, 2010, at 8:32 AM, Jay wrote:
> So what I'm looking for is readily available tools/packages that could
> produce some of the following:
> 3.6 Summary of Useful Commands (STATA: Source:
> * linktest--performs a link test for model specification, in our
> case to check if logit is the right link function to use. This command
> is issued after the logit or logistic command.
> and performs nonlinearity test.
> But, since I'm new to GLM, I owuld greatly appreciate how you/others
> go about and test the validity of a GLM model.
> On Feb 18, 1:18 am, Jay <josip.2... at gmail.com> wrote:
>> Are there any packages/functions available for testing the
>> underlying assumptions for a good GLM model? Like linktest in STATA
>> and smilar. If not, could somebody please describe their work process
>> when they check the validity of a logit/probit model?
David Winsemius, MD
West Hartford, CT
More information about the R-help