The timing (spacing) of assessments is an important component of longitudinal research. The purpose of the present study is to determine methods of timing the collection of longitudinal data that provide better parameter recovery in mixed effects nonlinear growth modeling. A simulation study was conducted, varying function type, as well as the number of measurement occasions, in order to examine the effect of timing on the accuracy and efficiency of parameter estimates. The number of measurement occasions was associated with greater efficiency for all functional forms and was associated with greater accuracy for the intrinsically nonlinear functions. In general, concentrating measurement occasions toward the left or at the extremes was associated with increased efficiency when estimating the intercepts of intrinsically linear functions, and concentrating values where the curvature of the function was greatest generally resulted in the best recovery for intrinsically nonlinear functions. Results from this study can be used in conjunction with theory to improve the design of longitudinal research studies. In addition, an R program is provided for researchers to run customized simulations to identify optimal sampling schedules for their own research.