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.ps...@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...@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. > [[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.
