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 > [[alternative HTML version deleted]]
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