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   0.319305815 1.818685 -1.160422
  2   0.287954733 1.716171 -1.163865
  3   0.054934676 1.448282 -1.360107
  4   0.001274279 1.548561 -1.419932
  5   0.087703116 1.448348 -1.450653
  6   0.034353299 1.563228 -1.428815
  7   0.008824320 1.433124 -1.449002
  8  -0.218615435 1.267652 -1.717512
  9  -0.181019998 1.316339 -1.692194
  10 -0.227707632 1.229211 -1.579833