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   0.322506047 1.806669 -1.154082
  2   0.285629074 1.726159 -1.144380
  3   0.055158869 1.443915 -1.348329
  4   0.005072463 1.540368 -1.404610
  5   0.089313444 1.458864 -1.444145
  6   0.030850858 1.554769 -1.402090
  7   0.013920725 1.428768 -1.442980
  8  -0.216355513 1.276630 -1.688061
  9  -0.195913195 1.332680 -1.687023
  10 -0.230126112 1.244005 -1.566616