[R] question about se of predicted glm values
Hey, all. I had a quick question about fitting new glm values and then looking at the error around them. I'm working with a glm using a Gamma distribution and a log link with two types of treatments. However, when I then look at the predicted values for each category, I find for the one that is close to 0, the error (using se.fit=T with predicted) actually makes it overlap 0. This is not possible, as non-0 values have no meaning. Am I missing something in the interpretation? I'm sure I am. Is there are better way to plot this that is accurate? Below is some sample code for an example problem. Note that the error for the value for category a (plotted at the end) does cross 0. Note: this is a simple example. The model I'm using has covariates, etc, but, I wanted to work out the correct method for the simple example so that I could take it back to my more complex model. Thanks! #data x-as.factor(c(rep(a,4),rep(b,4))) y-c(0.5,2,0.3,1.2,32.6,43,23.8,2.92) #plot the raw data plot(y ~ as.factor(x)) #fit a glm my.glm-glm(y ~ x, family=Gamma(link=log)) #get predicted values and their error a.fit-predict(my.glm, data.frame(x=a), se.fit=T) b.fit-predict(my.glm, data.frame(x=b), se.fit=T) #visualize it and see the SE cross 0 plot(1:2,c(a.fit$fit,b.fit$fit), pch=19, ylim=c(-2,4)) segments(1:2, c(a.fit$fit-a.fit$se.fit, b.fit$fit-b.fit$se.fit), 1:2, c(a.fit$fit+a.fit$se.fit, b.fit$fit+b.fit$se.fit)) lines(0:3,rep(0,4), lty=2) -Jarrett Jarrett Byrnes Population Biology Graduate Group, UC Davis Bodega Marine Lab 707-875-1969 http://www-eve.ucdavis.edu/stachowicz/byrnes.shtml [[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.
Re: [R] question about se of predicted glm values
G'day Jarrett, tapply(y,x,mean) a b 1.00 25.58 On Mon, 5 May 2008 20:21:26 -0700 Jarrett Byrnes [EMAIL PROTECTED] wrote: Hey, all. I had a quick question about fitting new glm values and then looking at the error around them. I'm working with a glm using a Gamma distribution and a log link with two types of treatments. However, when I then look at the predicted values for each category, I find for the one that is close to 0, And this does not surprise you, since with your data: tapply(y,x,mean) a b 1.00 25.58 So wouldn't you expect one predicted value to be close to 1 instead of zero? the error (using se.fit=T with predicted) actually makes it overlap 0. This is not possible, as non-0 values have no meaning. Am I missing something in the interpretation? Yes. :) For GLMs, predict returns by default the predicted values on the linear predictor scale, not on the response scale. Negative values for the linear predictor are, of course, possible and may have meaning. Look closely at the pictures that you have created. In the first one, for x=b, the values are around 30, in the picture with the fitted value the prediction for x=b is around 3; clearly another scale (namely the scale of the linear predictor). #get predicted values and their error a.fit-predict(my.glm, data.frame(x=a), se.fit=T) b.fit-predict(my.glm, data.frame(x=b), se.fit=T) Try: a.fit-predict(my.glm, data.frame(x=a), se.fit=T, type=response) b.fit-predict(my.glm, data.frame(x=b), se.fit=T, type=response) Hope this helps. Best wishes, Berwin === Full address = Berwin A TurlachTel.: +65 6515 4416 (secr) Dept of Statistics and Applied Probability+65 6515 6650 (self) Faculty of Science FAX : +65 6872 3919 National University of Singapore 6 Science Drive 2, Blk S16, Level 7 e-mail: [EMAIL PROTECTED] Singapore 117546http://www.stat.nus.edu.sg/~statba __ 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.
