School accountability is subject to considerable scrutiny. It generates sharp political debate, policy challenges, and continuous discussion. Growth models are now a part of that discussion. To many practitioners the sheer volume of "important to know" information is daunting. The members of the Technical Issues in Large Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR) state collaboratives have recognized the challenge of communicating detailed, technically-oriented measurement issues. In response, these groups have produced a series of publications aimed at providing technical and non-technical users with practical guidance about growth models. This publication continues the series by summarizing the "Growth Model Comparison Study: Practical Implications of Alternative Models for Evaluating School Performance" conducted by Pete Goldschmidt, Kilchan Choi, and J.P. Beaudoin which implemented statistical growth models using real student data from four states. The study is important because it is the first designed to make it possible to see whether results are different or similar when (a) the same growth models are estimated in different states and (b) different models are estimated in the same state. As a summary, this document is intended to provide timely and comprehensible information for practitioners and other stakeholders who may not have a technical background in using assessment data for educational accountability. (Contains 1 table and 44 footnotes.) [This paper was prepared for and commissioned by the Technical Issues in Large Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR) members of the system of State Collaboratives on Assessment and Student Standards (SCASS). It was written with the support of Charlene Tucker, Duncan MacQuarrie, and Doug Rindone and offers a summary of "Growth Model Comparison Study: Practical Implications of Alternative Models for Evaluating School Performance" (ED542761).]