Fitting lmer() model help

Machine Learning and Modeling
,
18

Hi Alexandre,

Thank you for your response.
I have scaled but I have possibly not done it correctly?
I used the scale function on the numeric values in the dataset (this excluded PPT and Intervention)

ind<-sapply(DATA, is.numeric)
DATA[ind] <- lapply(DATA[ind], scale)

and similar warnings come up with or without the scales variables

Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge with max|grad| = 0.050911 (tol = 0.002, component 1)
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model is nearly unidentifiable: very large eigenvalue
 - Rescale variables?
3: In as_lmerModLT(model, devfun) :
  Model may not have converged with 1 eigenvalue close to zero: 5.7e-11

I have also used this coding to try scaling incase it was my coding which was the problem

NumDATA<-DATA[,c(3:13)]
scaled<-scale(NumDATA)
PPT_and_Intervention<-DATA[,c(1,2)]
DATASCALED<-cbind(PPT_and_Intervention,scaled)

and a similar warning comes up

Warning messages:
1: In optwrap(optimizer, devfun, getStart(start, rho$lower, rho$pp),  :
  convergence code -4 from nloptwrap
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  unable to evaluate scaled gradient
3: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge: degenerate  Hessian with 1 negative eigenvalues
4: In as_lmerModLT(model, devfun) :
  Model may not have converged with 1 eigenvalue close to zero: 4.8e-09