Hello I am using glmmBUGS to fit a multilevel model. Treatments are nested in Course are nested in Patients. The predicted variable in total EEG duration. The predictors are:
at the observation level : Medication dose at the Course level: Weight in KG and Age at the Patient level: Weight in KG and Age I am trying to fit a multilevel model as in lmer, but in BUGS. Here is an example of the model I want to run: Linear mixed model fit by REML Formula: totalEEG ~ workDose + (1 + WEIGHTKG + AgeYrs | MRN/COURSE) Data: book AIC BIC logLik deviance REMLdev 7041 7112 -3506 7004 7011 Random effects: Groups Name Variance Std.Dev. Corr COURSE:MRN (Intercept) 6.5755e-06 2.5643e-03 WEIGHTKG 1.9015e-11 4.3606e-06 -1.000 AgeYrs 1.1138e-09 3.3373e-05 -1.000 1.000 MRN (Intercept) 5.0897e+02 2.2560e+01 WEIGHTKG 2.8231e-02 1.6802e-01 -1.000 AgeYrs 8.1881e-04 2.8615e-02 1.000 -1.000 Residual 2.4965e+02 1.5800e+01 Number of obs: 818, groups: COURSE:MRN, 114; MRN, 103 Fixed effects: Estimate Std. Error t value (Intercept) 51.721608 1.669860 30.974 workDose -0.010632 0.003246 -3.275 Correlation of Fixed Effects: (Intr) workDose -0.663 bgs.toteeg<-glmmBUGS(data=book, observations="totalEEG", covariates=list(MRN="AgeYrs", COURSE="WEIGHTKG", observations="workDose"), effects=c("MRN", "COURSE"), family="gaussian", modelFile="model.bug") however, this is failing with: Error in glmmBUGS(data = book, observations = "totalEEG", covariates = list(MRN = "AgeYrs", : unused argument(s) (observations = "totalEEG", covariates = list(MRN = "AgeYrs", COURSE = "WEIGHTKG")) I have already run models with multiple predictors at the lowest level. glmmBUGS parameterises and runs a WINBUGS model fine. however, this full mixed model seems not to work. When I tried: > bgs.toteeg<-glmmBUGS(data=book, totalEEG~workDose, reparam=c(MRN="AgeYrs", > COURSE="WEIGHTKG"), effects=c("MRN", "COURSE"), family="poisson", > modelFile="model.bug") IT compiled the WinBUGS model fine, but winBUGS stalled on an error, not recognising a node "xobservations". I'm learning, so it's not just a case where I can "step-up" and model it directly in Winbugs. R 2.13.2 on Win 7 i3Intel with lmer, nlme, R2WinBUGS, BRugs, lattice, attached. Winbugs version 14.3. (Which I know is working fine - Brainware problem most likely) Thank you Ross ross.du...@tcd.ie -- View this message in context: http://r.789695.n4.nabble.com/glmmBUGS-fails-to-accept-higher-level-covariates-tp3945251p3945251.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.