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
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