Evaluating the Adaptive Measurement of Change in the Presence of Item Parameter Estimation Error

Adaptive measurement of change (AMC) is a burgeoning psychometric method for measuring individual change trajectories. Previous simulations evaluating this method have all assumed that the parameters for test items are known. We evaluated the robustness of AMC hypothesis tests when using items with increasing amounts of estimation error.