?relevel Also, you might want to fit the models as follows
Model1 <- glm.nb(Cells ~ Cryogel*Day, data = myData) myData2 <- within(myData, Cryogel <- relevel(Cryogel, ref = "2")) Model2 <- update(Model1, data = myData1) &c You should always spedify the data set when you fit a model if at all possible. I would recommend you NEVER use attach() to put it on the search path, (under all but the most exceptional circumstances). You could fit your model as Model0 <- glm.nv(Cells ~ interaction(Cryogel, Day) - 1, data = myData) This will give you the subclass means as the regression coefficients. You can then use vcov(Model0) to get the variance matrix and compare any two you like using directly calculated t-statistics. This is pretty straightforward as well. Bill Venables. -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of bryony Sent: Tuesday, 17 May 2011 3:46 AM To: r-help@r-project.org Subject: [R] Post-hoc tests in MASS using glm.nb I am struggling to generate p values for comparisons of levels (post-hoc tests) in a glm with a negative binomial distribution I am trying to compare cell counts on different days as grown on different media (e.g. types of cryogel) so I have 2 explanatory variables (Day and Cryogel), which are both factors, and an over-dispersed count variable (number of cells) as the response. I know that both variables are significant, and that there is a significant interaction between them. However, I seem unable to generate multiple comparisons between the days and cryogels. So my model is Model1<-glm.nb(Cells~Cryogel+Day+Day:Cryogel) The output gives me comparisons between levels of the factors relative to a reference level (Day 0 and Cryogel 1) as follows: Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 1.2040 0.2743 4.389 1.14e-05 *** Day14 3.3226 0.3440 9.658 < 2e-16 *** Day28 3.3546 0.3440 9.752 < 2e-16 *** Day7 3.3638 0.3440 9.779 < 2e-16 *** Cryogel2 0.7097 0.3655 1.942 0.05215 . Cryogel3 0.7259 0.3651 1.988 0.04677 * Cryogel4 1.4191 0.3539 4.010 6.07e-05 *** Day14:Cryogel2 -0.7910 0.4689 -1.687 0.09162 . Day28:Cryogel2 -0.5272 0.4685 -1.125 0.26053 Day7:Cryogel2 -1.1794 0.4694 -2.512 0.01199 * Day14:Cryogel3 -1.0833 0.4691 -2.309 0.02092 * Day28:Cryogel3 0.1735 0.4733 0.367 0.71395 Day7:Cryogel3 -1.0907 0.4690 -2.326 0.02003 * Day14:Cryogel4 -1.2834 0.4655 -2.757 0.00583 ** Day28:Cryogel4 -0.6300 0.4591 -1.372 0.16997 Day7:Cryogel4 -1.3436 0.4596 -2.923 0.00347 ** HOWEVER I want ALL the comparisons e.g. Cryogel 2 versus 4, 3 versus 2 etc on each of the days. I realise that such multiple comparsions need to be approached with care to avoid Type 1 error, however it is easy to do this in other programmes (e.g. SPSS, Genstat) and I'm frustrated that it appears to be difficult in R. I have tried the glht (multcomp) function but it gives me the same results. I assume that there is some way of entering the data differently so as to tell R to use a different reference level each time and re-run the analysis for each level, but don't know what this is. Please help! Many thanks for your input Bryony -- View this message in context: http://r.789695.n4.nabble.com/Post-hoc-tests-in-MASS-using-glm-nb-tp3526934p3526934.html Sent from the R help mailing list archive at Nabble.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. ______________________________________________ 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.
