There's also a big difference in plot 2 (Normal Q-Q) in my real data, but I don't see a real difference in plot 2 for the example I sent, except that some of the outlier labels are different. Would the residuals being plotted likely be the cause of the difference in plot 2 as well? Dr. Snow, would you want to be able to see the plot 2 graphs for my real data? I don't know how to save plot 2 when I'm clicking through the plot(model) graphs, so I can't just send it to you. Thanks for checking this out Dr. Snow!
On Wed, Nov 12, 2008 at 11:05 AM, Greg Snow <[EMAIL PROTECTED]> wrote: > From a quick look at the code it looks like when you ask for plot number 5 > (included in default when 'which' is not specified), then the deviance > residuals are replaced by the pearson residuals to be used in later > computations. So the difference that you are seeing is that one of the > plots is based on deviance residuals and the other on pearson residuls. > > It seems that there is a bug here in that, at a minimum, the label should > be changed to indicate which residuals were actually used, or the code > changed to continue to use the deviance residuals for plot 3 even when plot > 5 is requested. > > Does anyone else see something that I missed in how the residuals are > replaced and used? > > -- > Gregory (Greg) L. Snow Ph.D. > Statistical Data Center > Intermountain Healthcare > [EMAIL PROTECTED] > 801.408.8111 > > > > -----Original Message----- > > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > > project.org] On Behalf Of Effie Greathouse > > Sent: Wednesday, November 12, 2008 11:16 AM > > To: r-help@r-project.org > > Subject: Re: [R] different results with plot.lm vs. plot.lm(which=c(2)) > > > > Hi Dr. Ripley--Sorry for the repost everybody. The original message I > > sent > > never showed up in my inbox, so I thought it didn't get sent to the > > list. > > > > I'm running R 2.8.0, installed from a pre-compiled version, on Windows > > XP. > > When I type Sys.getlocale() at the R prompt, it returns: > > "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United > > States.1252;LC_MONETARY=English_United > > States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252" > > > > Here's an example: > > bob <- seq(1:100) > > bob2 <- rgamma(100, 2, 1)*10+bob > > model<-glm(bob2 ~ bob, family=Gamma) > > > > Then enter: > > plot(model, which=c(3)) > > to get the Scale-Location graph > > > > Then compare it to the Scale-Location graph when you run the following > > command and page through to the 3rd graph: > > plot(model) > > > > When I do this, I get different results -- some of the high values are > > different on each plot. On my real data the difference is more severe > > than > > in this randomly generated example. I'd be happy to supply my real > > data and > > R code if this smaller example isn't sufficient. Thank you for any > > help!! > > > > > > On Wed, Nov 12, 2008 at 9:43 AM, Prof Brian Ripley > > <[EMAIL PROTECTED]>wrote: > > > > > Instead of re-posting the same message, please study the posting > > guide and > > > supply the information asked for, including a reproducible example. > > There is > > > no way we can help you unless you help us to help you. > > > > > > > > > On Wed, 12 Nov 2008, Effie Greathouse wrote: > > > > > > I am running GLM models using the gamma family. For example: > > >> model <-glm(y ~ x, family=Gamma(link="identity")) > > >> > > >> I am getting different results for the normal Q-Q plot and the > > >> Scale-Location plot if I run the diagnostic plots without specifying > > the > > >> plot vs. if I specify the plot ... e.g., "plot(model)" gives me a > > >> different > > >> Normal Q-Q graph than "plot(model, which=c(2))". The former gives > > data > > >> points distributed in a quadratic pattern, while the latter gives > > data > > >> points more or less along the 1:1 line. Shouldn't these two > > commands be > > >> giving me the same exact graphs? I have read the documentation on > > plot.lm > > >> and searched the help archives, but I am still learning GLM's and > > I'm not > > >> very familiar with understanding diagnostic plots for GLM's, so any > > help > > >> would be much appreciated! > > >> > > >> [[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<http://www.r-project.org/posting-guide.html> > <http://www.r- > > project.org/posting-guide.html> > > >> and provide commented, minimal, self-contained, reproducible code. > > >> > > > > > > -- > > > Brian D. Ripley, [EMAIL PROTECTED] > > > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > > > University of Oxford, Tel: +44 1865 272861 (self) > > > 1 South Parks Road, +44 1865 272866 (PA) > > > Oxford OX1 3TG, UK Fax: +44 1865 272595 > > > > > > > [[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-<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.
