Iterative Estimation of Parameters in Multilevel Models with Measurement Errors

Although the measurement error exists in the most scientific experiments، in order to simplify the modeling، its presence is usually ignored in statistical studying. In this paper، various approaches on estimating the parameters of multilevel models in presence of measurement error are studied. In addition، to improve the parameter estimates in this case، a new method is proposed which has high precision and reasonable convergence rate in compare with previous common approaches. Also، the performance of the proposed method as well as usual approaches are evaluated and compared using simulation study and analyzing real data of the income-expenditure of some households in Tehran city in 2008.