An attempt to lower sources of systematic measurement error using Hierarchical Generalized Linear Modeling (HGLM).

The purpose of the present studies was to test the effects of systematic sources of measurement error on the parameter estimates of scales using the Rasch model. Studies 1 and 2 tested the effects of mood and affectivity. Study 3 evaluated the effects of fatigue. Last, studies 4 and 5 tested the effects of motivation on a number of parameters of the Rasch model (e.g., ability estimates). Results indicated that (a) the parameters of interest and the psychometric properties of the scales were substantially distorted in the presence of all systematic sources of error, and, (b) the use of HGLM provides a way of adjusting the parameter estimates in the presence of these sources of error. It is concluded that validity in measurement requires a thorough evaluation of potential sources of error and appropriate adjustments based on each occasion.