In dealing with parametric nonlinear mixed effects models, intensive numerical integration often makes exact maximum likelihood estimation impractical given the current computing capacity. Algorithms based on linearization, such as the first order method and the conditional first order method, have the potential of producing highly inconsistent estimates, although numerically they are more effi...
