The recent development of multilevel IRT models (Fox & Glas, 2001, 2003) has been shown to be very useful for analyzing relationships between observed variables on different levels containing measurement error. Model parameter estimates and their standard deviations are concurrently estimated taking account of measurement error in observed variables. The multilevel IRT models are, in particular, useful in the analysis of school effectiveness research data since hierarchical structured educational data are subject to error. By re-examining some school effectiveness studies, the basic aspects of this new model and consequences of measurement error are shown.