predict2.md
In merTools: Tools for Analyzing Mixed Effect Regression Models

Prediction intervals work with new factor levels added

Code
  predictInterval(glmer3LevSlope, newdata = zNew)
Condition
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning in `chol.default()`:
  the matrix is either rank-deficient or not positive definite
  Warning:
       The following levels of BROOD from newdata 
   -- 100, 101 -- are not in the model data. 
       Currently, predictions for these values are based only on the 
   fixed coefficients and the observation-level error.
Output
              fit      upr       lwr
  1   0.319307693 1.818687 -1.160420
  2   0.287956853 1.716173 -1.163863
  3   0.054937049 1.448286 -1.360102
  4   0.001277092 1.548562 -1.419931
  5   0.087706377 1.448351 -1.450651
  6   0.034355538 1.563231 -1.428813
  7   0.008824511 1.433126 -1.449001
  8  -0.218614810 1.267654 -1.717510
  9  -0.181019085 1.316341 -1.692193
  10 -0.227707173 1.229211 -1.579832