##Loading and sorting out data set.
 options(warn=-1)
  rm(model.half) # remove existing models.
  rm(model.full)
  rm(model.null)
  options(warn=0)

  # Create procedural names
  anovaname = substr(datnames[i], 1, nchar(datnames[i])-4)

  # Remove L&R designations. Format all to factors.
  data=read.csv(datfiles[i])
  data$ROI =as.character(data$ROI)
  data$ROI = str_remove(data$ROI,"L_|R_|R|L")

  data$ROI =as.factor(data$ROI)
  data$Condition = as.factor(data$Condition)
  data$Part = as.factor(data$Part)
  data$hem = as.factor(data$hem)


## This works. Same LMM set up, using LMER. Don't run it, it takes like 10 hours.

model.full <- lmer(Values ~ Condition*ROI*hem + (Condition+ROI+hem|Part),data, REML=FALSE)

## However this does not. It used to, but no longer. I was hoping to use this for  post hoc tests etc.

ges.peak <- aov_4(Values ~ Condition*ROI*hem + (Condition+ROI+hem|Part), data, fun_aggregate = mean)