The answer to your first question is "yes, the order does make a
difference." I have not worked with lmer, but the standard anova applied
to lm() will provide what are called Type I sums of squares. Each effect
is adjusted for all prior effects.
Look at John Fox's car package. I don't know if it will handle lmer
models, but it is worth trying. Note that for car the function is Anova,
not anova.
Good luck,
Dave Howell
Gilles San Martin wrote:> Dear R user
>
> I have 2 problems with lmer.
> The statistical consultance service of my university has recomended to me
to
> expose those problems here.
>
> Sorry for this quite long message.
> Your help will be greatly appreciated...
>
> Gilles San Martin
>
>
> 1) anova()
>
> I fit a first model :
> model1 <- lmer(eclw~1 + density + landsc + temp + landsc:temp +
(1|region) +
> (1|region:pop) + (1|region:pop:family), data=fem1)
>
> I fit the same model but I'm just changing the order of 2 fixed factors
> (here : "temp" and "landsc") :
> model2 <- lmer(eclw~1 + density + temp + landsc + landsc:temp +
(1|region) +
> (1|region:pop) + (1|region:pop:family), data=fem1)
>
> Then, if I apply the anova() function on these 2 models, the given Sum of
> Squares are different for the fixed effects whose place has been changed:
>
>> anova(model1)
> Analysis of Variance Table
> Df Sum Sq Mean Sq
> density 1 21941.3 21941.3
> landsc 1 4800.7 4800.7
> temp 1 10119.9 10119.9
> landsc:temp 1 292.2 292.2
>
>> anova(model2)
> Analysis of Variance Table
> Df Sum Sq Mean Sq
> density 1 21941.3 21941.3
> temp 1 10441.1 10441.1
> landsc 1 4479.5 4479.5
> temp:landsc 1 292.2 292.2
>
> How is it possible? Do the fixed effects need to be writen in a particular
> order ?
> My dataset is unbalanced. Somebody tells to me that this could have some
> importance for this problem.
>
>
>
> 2) syntax
>
> I have a quite complex model and we have not been able to find accurate
> documentation about the syntax corresponding to my model.
>
> I have :
> - 2 fixed factors : "landsc" & "temp" and their
interaction " landsc:temp"
> - 1 continuous covariate considered as fixed
> - 3 nested random factors : "region", "pop" and
"family" with family nested
> in pop and pop nested in region*landsc
>
> I'm mainly interrested in the effect of "landsc" ane
"landsc:temp" on the
> variable I'm studying.
>
> I had used the following synthax :
> model3 <- lmer(eclw~1 + density + landsc + temp + landsc:temp +
(1|region) +
> (1|region:pop) + (1|region:pop:family), data=fem1)
>
> But somebody told to me that the folowing one could be more correct , and
> I'm in doubt now:
> model4 <- lmer(eclw~1 + density + landsc + temp + landsc:temp +
(1|region) +
> (pop|region) + (family|pop), data=fem1)
>
> The variables are coded with unique levels from inner nested factors as
> recomended here (Bates & Pinheiro : lme for SAS PROC MIXED users) :
>
http://biostat.hitchcock.org/FacultyandStaff/OnlineManuals/PDF%20Files/lmesas.pdf
>
> Which syntax is the right one and describe de nested structure correctly?
> And what could be the meaning of the wrong model?
> Is there somewhere general information about lmer synthax that we could
have
> missed (not just simple examples)?
> (I just have an article D. Bates from Rnews vol5/1 and a book of Mr Galwey
> in addition to the lme4 package help).
>
>
> I have also tried lme (without the covariate) :
> But the denominator DF seem very strange to me considering the containment
> method that is used, so I wonder also if the syntax that I use is correct :
>
>> model5 <-lme(eclw~landsc + temp + landsc*temp , random= ~
>> 1|region/pop/family ,method="REML", data=femr)
>> anova.lme(model5)
> numDF denDF F-value p-value
> (Intercept) 1 332 546.0825 <.0001
> landsc 1 9 2.8841 0.1237
> temp 1 332 25.7565 <.0001
> landsc:temp 1 332 0.4316 0.5117
>
> The number of levels of the factors are : temp : 2 ; landsc : 2 ; region :
2
> ; pop : 12 ; family : 34
> If I'm not wrong the containment method use the same denominator DF as
the
> classical Anova approach.
> So here landsc would have to be tested against landsc*region with (2-1) *
> (2-1) = 1 denominator DF.
> And the same for temp...
>
>
>
>
> ________________________________
>
> Gilles San Martin y Gomez
>
> Biodiversity Research Centre
> Ecology & Biogeography Unit
> University of Louvain-La-Neuve (UCL)
> Croix du Sud 4/5
> B-1348 Louvain-la-Neuve
> Belgium
>
> Tel. +32 (0)10 47 21 73
> E-mail: gilles.sanmartin at gmail.com
>
> ______________________________________________
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
David C. Howell
PO Box 770059
627 Meadowbrook Circle
Steamboat Springs, CO
80477