r - How to predict values by using a model developed by linear mixed modelling with nesting effect? -

i have model developed using 5 variables in r. linear mixed modelling method selected develop model nesting effect.

my r code model development below:

model1 <- lmer(reduction.factor ~ (1|pai:open.wind) +       (1|pai:temp) + (1|pai:height)+ (1|pai:density)+ pai  ,     data = model) 

4 parameters nested pai.

to see how model predict in different conditions, have created different numbers 5 parameters data frame (called "case study").

it looks this:

temp    height  density pai open wind 20.000  0.041   0.033   1.960   30.000 20.000  0.082   0.061   1.960   30.000 20.000  0.122   0.059   1.960   30.000 20.000  0.163   0.061   1.960   30.000 20.000  0.204   0.043   1.960   30.000 20.000  0.245   0.048   1.960   30.000 20.000  0.286   0.052   1.960   30.000 40.000  0.082   0.061   1.960   40.000 40.000  0.122   0.059   1.960   40.000 40.000  0.163   0.061   1.960   40.000 40.000  0.204   0.043   1.960   40.000 40.000  0.245   0.048   1.960   40.000 40.000  0.286   0.052   1.960   40.000 

i wanted predict 'reduction.factor' using values of 5 parameters.

so put p1 <- predict(model1,case study) see predictions.. error in (function (x, n) : new levels detected in newdata <- message came up..

how can predict 'reduction.factor' using values 5 parameters? and.. if want have confidence interval (95%), should put 'interval='confidence''?

thank in advance.