Lmer and variance-covariance matrix
On Thu, Mar 3, 2011 at 7:03 AM, Antoine Paccard
<antoine.paccard at unine.ch> wrote:
Dear modelers, I have been trying in the past few months to obtain a variance- covariance matrix using lmer. I failed multiple times until I decided to do it under SAS. Now, I am going back on it and would like to run it with R. I measured 15 different traits and my data is organized this way: fam ? ? id ? ? trait ? ? score 57 ? ? 1 ? ? 1 ? ? 0.047207645 57 ? ? 2 ? ? 1 ? ? 1.420790311 57 ? ? 3 ? ? 1 ? ? -0.290782077 57 ? ? 1 ? ? 2 ? ? -0.585655473 57 ? ? 2 ? ? 2 ? ? -0.986483343 57 ? ? 3 ? ? 2 ? ? 0.290187057 57 ? ? 1 ? ? 3 ? ? 0.741162271 57 ? ? 2 ? ? 3 ? ? 1.59448736 57 ? ? 3 ? ? 3 ? ? . . ? ? . ? ? . ? ? . . ? ? . ? ? . ? ? . . ? ? . ? ? . ? ? . 57 ? ? 1 ? ? 15 ? ? . 57 ? ? 2 ? ? 15 ? ? . 57 ? ? 3 ? ? 15 ? ? . 58 ? ? 1 ? ? 1 ? ? . 58 ? ? 2 ? ? 1 ? ? . 58 ? ? 3 ? ? 1 ? ? . . ? ? . ? ? . ? ? . . ? ? . ? ? . ? ? . . ? ? . ? ? . ? ? . 58 ? ? 1 ? ? 15 ? ? . 58 ? ? 2 ? ? 15 58 ? ? 3 ? ? 15 . . . 100 ? ? 1 ? ? 15 100 ? ? 2 ? ? 15 100 ? ? 3 ? ? 15 with ?fam? being the family, ?id? the individual, ?trait? the traits measured and ?score? the result of each measures. So far I have been trying to fit this model: d <- data d$fam1 <- factor(d$fam) d$id1 <- factor(d$id) d$trait1 <- factor(d$trait) w.family <- lmer(score ~ (trait1 | fam1/id1 ), data=d)
But I was getting some ?stack overflow? error messages so I ran the model this way: w.family <- lmer(score ~ (trait1 | fam1/id1 ), data=d,control = list (maxIter = 500))
If there are 15 levels of trait you are trying to estimate 240 variance-covariance parameters (120 for fam1 and 120 for fam1:id1). That is a very large optimization problem, I'm not surprised that there is difficulty in finding the optimum.
Although it still didn?t work and I am now wondering what is wrong in this model. The reason why I have put ?trait1? in the random effect is because it was the only way for me to obtain a variance-covariance matrix on all my traits. I am currently trying to put ?trait1? also as fixed effect: w.family <- lmer(score ~ trait1 + (trait1 | fam1/id1 ), data=d,control = list (maxIter = 500)) I would be curious to know what you think about such a model and why it actually doesn?t work. Moreover, I am trying to write done the equation for the model: w.family <- lmer(score ~ (trait1 | fam1/id1 ), data=d) but can?t figure it out. I know I should get something as: Scoreij = ? + fam(i) + Ij(i) + ? But I am not sure if that?s right. What do you think? Thanks a lot for your help, Best, Antoine Paccard ----------- Antoine Paccard, Laboratory of Evolutionary Botany, Institut of biology, Facult? des Sciences, University of Neuch?tel, Unimail, Rue ?mile-Argand 11, 2000, Neuch?tel Switzerland Office: (0041) (0)32 718 23 49 Fax: (0041) (0)32 718 30 01 www.unine.ch/members/antoine.paccard/ http://www2.unine.ch/evobot ? ? ? ?[[alternative HTML version deleted]]
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