Dear list members, the following hlm was constructed:
hlm <- groupedData(laut ~ design | grpzugeh, data = imp.not.I) the grouped data object is located at and can be downloaded: www.anicca-vijja.de/lg/hlm_example.Rdata The following works: library(nlme) summary( fitlme <- lme(hlm) ) with output: ... AIC BIC logLik 425.3768 465.6087 -197.6884 Random effects: Formula: ~design | grpzugeh Structure: General positive-definite StdDev Corr (Intercept) 0.3772478 (Intr) dsgn:8 dsgn:7 designmit:8 0.6776543 0.183 designohne:7 0.6619983 -0.964 0.086 designohne:8 1.0680576 -0.966 0.077 1.000 Residual 1.3468816 Fixed effects: laut ~ design Value Std.Error DF t-value p-value (Intercept) 3.857143 0.2917529 102 13.220579 0.0000 designmit:8 -0.285714 0.4417919 102 -0.646717 0.5193 designohne:7 -0.107143 0.4383878 102 -0.244402 0.8074 designohne:8 0.607143 0.5408713 102 1.122527 0.2643 Correlation: (Intr) dsgnm:8 dsgn:7 designmit:8 -0.451 designohne:7 -0.775 0.363 designohne:8 -0.763 0.304 0.699 Standardized Within-Group Residuals: Min Q1 Med Q3 Max -2.5074669 -0.4530573 0.1755326 0.5837670 2.3700004 Number of Observations: 112 Number of Groups: 7 The following does _not_ work and leads to a convergence error: fitlme1 <- lme(laut ~ design, random = ~ design | grpzugeh, data = hlm) Fehler in lme.formula(laut ~ design, random = ~design | grpzugeh, data = hlm) : iteration limit reached without convergence (9) This was tried with R : Copyright 2005, The R Foundation for Statistical Computing Version 2.2.0 (2005-10-06 r35749) Using another R version (2.1.0, also windows with nlme version built under R 2.1.1) , it works. Thus, what's the problem then? I tried without the random effects, i.e. random = ~ 1 | grpzugeh This works. Comparing both calls on the version R2.1.0 that goes well, the following differences in the output of the random effects can be identified: summary( fitlme <- lme(hlm) ) <--> Random effects: ... Structure: General positive-definite </--> compared to summary(lme(laut ~ design, random = ~ design | grpzugeh, data = hlm)) <--> Random effects: ... Structure: General positive-definite, Log-Cholesky parametrization </--> The estimates of the fixed effects are similar, the S.E.s not. The random effects are different, too. AIC/BIC/logLik are slightly different. Thus my question: 1) Do I have overseen a switch for the structure of the random effects? Is something wrong with the call/ formular? 2) What is the cause of the convergence error which seems to depend on the built of R/nlme? Thank you very much. Best wishes, leo gürtler -- email: [EMAIL PROTECTED] www: http://www.anicca-vijja.de/ ______________________________________________ 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