Hi Josh and Elaine: John Fox's CAR book ( the companion  to his applied
regression text ) is really great for implementing GLMs in R. It also has a
brief but quality discussion of the theory
behind them. His text goes into more detail. Dobson's "Introduction to
generalized linear models" is also decent. So is Faraway's text but I don't
remember the title.


Mark







On Sun, Oct 28, 20
12 at 11:25 PM, Joshua Wiley <jwiley.psych@gmail.com> wrote:

> Hi Elaine,
>
> If you want identical models, you need to use the same family and then
> the formula is the same.  Here is an example with a built in dataset:
>
>
> ## these two are identical
> > coef(lm(mpg ~ hp + log(wt), data = mtcars))
>  (Intercept)           hp      log(wt)
>  38.86095585  -0.02808968 -13.06001270
> > coef(glm(mpg ~ hp + log(wt), data = mtcars, family = gaussian))
>  (Intercept)           hp      log(wt)
>  38.86095585  -0.02808968 -13.06001270
>
> ## not identical
> > coef(glm(mpg ~ hp + wt, data = mtcars, family = gaussian(link = "log")))
> (Intercept)          hp          wt
>  3.88335638 -0.00173717 -0.20851238
>
> I show the log link because the poisson family default to a log link,
> but that is equivalent to:
> log(E(y)) = Xb
>
> where X is your design matrix (intercept, A, B, log(C), log(D) for
> you).  In short the link function operates on the outcome, not the
> predictors so even though the poisson family includes a log link, it
> will not yield the same results as a log transformation of two of your
> predictors.
>
> I do not have any online references off the top of my head, but it
> seems like you may be well served by reading some about generalized
> linear models and the concept of link functions.
>
> Cheers,
>
> Josh
>
>
> On Sun, Oct 28, 2012 at 8:01 PM, Elaine Kuo <elaine.kuo.tw@gmail.com>
> wrote:
> >
> > Hello list,
> >
> > I am running a regression using
> >
> > lm(Y~A+B+log(C)+log(D))
> >
> >
> > Now, I would like to test if glm can produce similar results.
> > So the code was revised as
> >
> > glm(Y~A+B+C+D, family=poisson) (code 1)
> >
> >
> > However, I found some example using glm for lm.
> > It suggests that the code should be revised like
> > glm(Y~A+B+log(C)+log(D), family=poisson) (code 2)
> >
> > Please kindly advise which  code is correct.
> > Thank you.
> >
> > Elaine
> >
> >         [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> Programmer Analyst II, Statistical Consulting Group
> University of California, Los Angeles
> https://joshuawiley.com/
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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