On 10/14/06, Spencer Graves <[EMAIL PROTECTED]> wrote: > You want to estimate a different 'cs' variance for each level of > 'trth', as indicated by the following summary from your 'fake data set': > > > tapply(dtf$x, dtf$trth, sd) > FALSE TRUE > 1.532251 8.378206 > > Since var(x[trth]) > var(x[!trth]), I thought that the following > should produce this: > > mod1.<-lmer( x ~ (1|rtr)+ (trth|cs) , data=dtf) > > Unfortunately, this generates an error for me: > > Error in lmer(x ~ (1 | rtr) + (trth | cs), data = dtf) : > the leading minor of order 1 is not positive definite > > I do not understand this error, and I don't have other ideas about > how to get around it using 'lmer'.
Hmm. It's an interesting problem. I can tell you where the error message originates but I can't yet tell you why. The error message originates when Cholesky decompositions of the variance-covariance matrices for the random effects are generated at the initial estimates. It looks as if one of the model matrices is not being formed correctly for some reason. I will need to do more debugging. > It seems to me that 'lme' in > library(nlme) should also be able to handle this problem, but 'lme' is > designed for nested factors, and your 'rtr' and 'cs' are crossed. If it > were my problem, I think I'd study ch. 4 and possibly ch. 5 of Pinheiro > and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer) on > 'pdMat' and 'corrStruct' classes, because I believe those may support > models with crossed random effects like in your example AND might also > support estimating different variance components for different levels of > a fixed effect like 'trth' in your example. > > If we are lucky, someone else might educate us both. > > I'm sorry I couldn't answer your question, but I hope these > comments might help in some way. > > Spencer Graves > > Frank Samuelson wrote: > > I have a model: > > mod1<-lmer( x ~ (1|rtr)+ trth/(1|cs) , data=dtf) # > > > > Here, cs and rtr are crossed random effects. > > cs 1-5 are of type TRUE, cs 6-10 are of type FALSE, > > so cs is nested in trth, which is fixed. > > So for cs I should get a fit for 1-5 and 6-10. > > > > This appears to be the case from the random effects: > > > mean( ranef(mod1)$cs[[1]][1:5] ) > > [1] -2.498002e-16 > > > var( ranef(mod1)$cs[[1]][1:5] ) > > [1] 23.53083 > > > mean( ranef(mod1)$cs[[1]][6:10] ) > > [1] 2.706169e-16 > > > var( ranef(mod1)$cs[[1]][6:10] ) > > [1] 1.001065 > > > > However VarCorr(mod1) gives me only > > a single variance estimate for the cases. > > How do I get the other variance estimate? > > > > Thanks for any help. > > > > -Frank > > > > > > > > My fake data set: > > ------------------------------------------- > > data: > > $frame > > x rtr trth cs > > 1 -4.4964808 1 TRUE 1 > > 2 -0.6297254 1 TRUE 2 > > 3 1.8062857 1 TRUE 3 > > 4 2.7273275 1 TRUE 4 > > 5 -0.6297254 1 TRUE 5 > > 6 -1.3331767 1 FALSE 6 > > 7 -0.3055796 1 FALSE 7 > > 8 1.3331767 1 FALSE 8 > > 9 0.1574314 1 FALSE 9 > > 10 -0.1574314 1 FALSE 10 > > 11 -3.0958803 2 TRUE 1 > > 12 12.4601615 2 TRUE 2 > > 13 -5.2363532 2 TRUE 3 > > 14 1.5419810 2 TRUE 4 > > 15 7.7071005 2 TRUE 5 > > 16 -0.3854953 2 FALSE 6 > > 17 0.7673098 2 FALSE 7 > > 18 2.9485984 2 FALSE 8 > > 19 0.3854953 2 FALSE 9 > > 20 -0.3716558 2 FALSE 10 > > 21 -6.4139940 3 TRUE 1 > > 22 -3.8162344 3 TRUE 2 > > 23 -11.0518554 3 TRUE 3 > > 24 2.7462631 3 TRUE 4 > > 25 16.2543990 3 TRUE 5 > > 26 -1.7353668 3 FALSE 6 > > 27 1.3521369 3 FALSE 7 > > 28 1.3521369 3 FALSE 8 > > 29 0.2054067 3 FALSE 9 > > 30 -1.7446691 3 FALSE 10 > > 31 -6.7468356 4 TRUE 1 > > 32 -11.3228243 4 TRUE 2 > > 33 -18.0088554 4 TRUE 3 > > 34 4.6264891 4 TRUE 4 > > 35 9.2973991 4 TRUE 5 > > 36 -4.1122576 4 FALSE 6 > > 37 -0.5091994 4 FALSE 7 > > 38 1.2787085 4 FALSE 8 > > 39 -1.6867089 4 FALSE 9 > > 40 -0.5091994 4 FALSE 10 > > > > ______________________________________________ > > R-help@stat.math.ethz.ch 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. > > > ______________________________________________ R-help@stat.math.ethz.ch 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.