Could you copy the data? Data <- data.frame(C.Mean,Mean.richness,Zoop,Diversity,Phyto) dput(Data)
I have the feeling something's wrong there. I believe you have 48 observations (47df + 1 for the intercept), 2 levels of Diversity, 4 of Phyto and 48/(3*4)=4 levels of Zoop. But you don't have 3df for Zoop. Either I'm way off, or what goes in the lm is not what you think it is. I tried a small sample with the datastructure I believe you have, but I couldn't reproduce your error. ## Run Phyto <- as.factor(rep(rep(c("A","B","C","D"),each=6),2)) Diversity <- as.factor(rep(c("High","Low"),each=24)) Zoop <- rep(c(1,2,3,4),times=12) C.Mean <- rnorm(48) Mean.richness <-rnorm(48) test <- lm(C.Mean~ Mean.richness + Diversity + Zoop + Diversity/Phyto + Zoop*Diversity/Phyto) Anova(test,type="III") Zoop <- as.factor(Zoop) Anova(test,type="III") ## End Run Cheers Joris On Thu, Jun 3, 2010 at 10:26 PM, Anita Narwani <anitanarw...@gmail.com>wrote: > I would just like to add that when I remove the co-variate of Mean.richness > from the model (i.e. eliminating the non-orthogonality), the aliasing > warning is replaced by the following error message: > "Error in t(Z) %*% ip : non-conformable arguments" > > That is when I enter this model: > carbonmean<-lm(C.Mean~ Diversity + Zoop + Diversity/Phyto + > Zoop*Diversity/Phyto) > > > > > > > > On Wed, Jun 2, 2010 at 6:05 PM, Joris Meys <jorism...@gmail.com> wrote: > >> that's diversity/phyto, zoop or phyto twice in the formula. >> >> >> On Thu, Jun 3, 2010 at 3:00 AM, Joris Meys <jorism...@gmail.com> wrote: >> >>> That's what one would expect with type III sum of squares. You have Phyto >>> twice in your model, but only as a nested factor. To compare the full model >>> with a model without diversity of zoop, you have either the combination >>> diversity/phyto, zoop/phyto or phyto twice in the formula. That's aliasing. >>> >>> Depending on how you stand on type III sum of squares, you could call >>> that a "bug". Personally, I'd just not use them. >>> >>> https://stat.ethz.ch/pipermail/r-help/2001-October/015984.html >>> >>> Cheers >>> Joris >>> >>> >>> On Thu, Jun 3, 2010 at 2:13 AM, Anita Narwani <anitanarw...@gmail.com>wrote: >>> >>>> Hello, >>>> >>>> I have been trying to get an ANOVA table for a linear model containing a >>>> single nested factor, two fixed factors and a covariate: >>>> >>>> carbonmean<-lm(C.Mean~ Mean.richness + Diversity + Zoop + >>>> Diversity/Phyto + >>>> Zoop*Diversity/Phyto) >>>> >>>> >>>> >>>> where, *Mean.richness* is a covariate*, Zoop* is a categorical variable >>>> (the >>>> species), *Diversity* is a categorical variable (Low or High), and >>>> *Phyto*(community composition) is also categorical but is nested >>>> within the level >>>> of *Diversity*. Quinn & Keough's statistics text recommends using Type >>>> III >>>> SS for a nested ANOVA with a covariate. >>>> >>>> I get the following output using the Type I SS ANOVA: >>>> >>>> >>>> >>>> Analysis of Variance Table >>>> Response: C.Mean >>>> Df Sum Sq >>>> Mean >>>> Sq F value Pr(>F) >>>> Mean.richness 1 56385326 56385326 >>>> 23.5855 3.239e-05 *** >>>> Diversity 1 14476593 >>>> 14476593 >>>> 6.0554 0.019634 * >>>> Zoop 1 13002135 >>>> 13002135 >>>> 5.4387 0.026365 * >>>> Diversity:Phyto 6 126089387 21014898 >>>> 8.7904 1.257e-05 *** >>>> Diversity:Zoop 1 263036 >>>> 263036 >>>> 0.1100 0.742347 >>>> Diversity:Zoop:Phyto 6 61710145 10285024 >>>> 4.3021 >>>> 0.002879 ** >>>> Residuals 31 74110911 >>>> 2390675 >>>> >>>> I have tried using both the drop1() command and the Anova() command in >>>> the >>>> car package. >>>> >>>> When I use the Anova command I get the following error message: >>>> >>>> >Anova(carbonmean,type="III") >>>> >>>> Error in linear.hypothesis.lm(mod, hyp.matrix, summary.model = sumry,: >>>> One >>>> or more terms aliased in model. >>>> >>>> >>>> >>>> I am not sure why this is aliased. There are no missing cells, and the >>>> cells >>>> are balanced (aside from for the covariate). Each Phyto by Zoop cross is >>>> replicated 3 times, and there are four Phyto levels within each level of >>>> Diversity. When I remove the nested factor (Phyto), I am able to get the >>>> Type III SS output. >>>> >>>> >>>> >>>> Then when I use drop1(carbonmean,.~.,Test=F) I get the following >>>> output: >>>> >>>> > drop1(carbonmean,.~.,Test="F") >>>> >>>> Single term deletions >>>> >>>> >>>> >>>> Model: >>>> >>>> C.Mean ~ Mean.richness + Diversity + Zoop + Diversity/Phyto + Zoop * >>>> Diversity/Phyto >>>> >>>> Df Sum of Sq >>>> RSS AIC >>>> >>>> <none> 74110911 718 >>>> >>>> Mean.richness 1 49790403 >>>> 123901314 >>>> 741 >>>> >>>> Diversity 0 0 >>>> 74110911 718 >>>> >>>> Zoop 0 0 >>>> 74110911 718 >>>> >>>> Diversity:Phyto 6 118553466 192664376 >>>> 752 >>>> >>>> Diversity:Zoop 0 -1.49e-08 >>>> 74110911 >>>> 718 >>>> >>>> Diversity:Zoop:Phyto 6 61710145 135821055 >>>> 735 >>>> >>>> >>>> >>>> There are zero degrees of freedom for Diversity, Zoop and their >>>> interaction, >>>> and zero sums of sq for Diversity and Zoop. This cannot be correct, >>>> however >>>> when I do the model simplification by dropping terms from the models >>>> manually and comparing them using anova(), I get virtually the same >>>> results. >>>> >>>> >>>> >>>> I would appreciate any suggestions for things to try or pointers as to >>>> what >>>> I may be doing incorrectly. >>>> >>>> >>>> >>>> Thank you. >>>> >>>> Anita Narwani. >>>> >>>> [[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. >>>> >>>> >>> >>> >>> -- >>> Joris Meys >>> Statistical Consultant >>> >>> Ghent University >>> Faculty of Bioscience Engineering >>> Department of Applied mathematics, biometrics and process control >>> >>> Coupure Links 653 >>> B-9000 Gent >>> >>> tel : +32 9 264 59 87 >>> joris.m...@ugent.be >>> ------------------------------- >>> Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php >>> >> >> >> >> -- >> Joris Meys >> Statistical Consultant >> >> Ghent University >> Faculty of Bioscience Engineering >> Department of Applied mathematics, biometrics and process control >> >> Coupure Links 653 >> B-9000 Gent >> >> tel : +32 9 264 59 87 >> joris.m...@ugent.be >> ------------------------------- >> Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php >> > > -- Joris Meys Statistical Consultant Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control Coupure Links 653 B-9000 Gent tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php [[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.