without being an expert for the specific lmer error code, it seems that your model matrix is singular, that is, not full rank. For that reason, X'X is not invertible, which means that there is no unique solution to the problem. Have you tried with x2 alone, without the interaction effect between x1 and x2, and with a level 1 random effect (intercept) only? That would give a hint where the singularity arises.
Best, Daniel ------------------------- cuncta stricte discussurus ------------------------- -----Ursprüngliche Nachricht----- Von: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Im Auftrag von Sachi Ito Gesendet: Sunday, June 28, 2009 6:05 PM An: r-help@r-project.org Betreff: [R] HLM - centering level 2 predictor Dear R-helpers, I'm analyzing a data with hierarchical linear model. I have one level 1 predictor and one level 2 predictor, which looks like below: fm1 <- lmer(y ~ 1 + x1 + x2 + x1:x2 + (1 + x1 | id.full)) where: y is the outcome variable. x1 is the level 1 predictor variable. x2 is the level 2 predictor variable. id.full is the conditioned variable. It runs beautifully when only x1 is centered (I subtracted the mean from each value). However, when I also center x2 variable with the same procedure, it gives me the following error message: Warning message: In mer_finalize(ans) : singular convergence (7) I'd appreciate if someone could explain me what it means. One of the differences between "non-centered values" and "centered values" is that the "centered values" include negative values. Could it be the reason? If so, what shall I do? Thank you! [[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. ______________________________________________ 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.
