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: [EMAIL PROTECTED] > > ______________________________________________ > 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. > -- David C. Howell PO Box 770059 627 Meadowbrook Circle Steamboat Springs, CO 80477 ______________________________________________ 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.
