High school dropout, enrollment, and graduation rates are important indicators of students' college and career readiness, which in turn significantly impact both individual income levels and the overall knowledge-driven economy. Despite the long-term benefits of a high school education, much of the current literature on raising school effectiveness excludes high schools. This has resulted in a lack of attention given to the unique challenges facing evaluation of school effectiveness at the high school level. Value-added analysis measures the contribution of education units (classrooms and schools) and agents (teachers and principals) to student performance by isolating their effects from external sources of student outcomes (e.g. prior knowledge and student characteristics). In practice, value-added models usually use the improvement of student performance on standardized tests as the student outcome measure. Value-added models attempt to identify the effects of schools and teachers by using statistical models, which in turn use available data to measure school effectiveness. However, substantial variation exists across specific value-added models, depending on the availability of data and the purpose of the value-added analysis. The value-added model for the 2011 National Center on Scaling Up (NCSU) initiative was developed using data from the Fort Worth Independent School District (FWISD) of Texas. The FWISD value-added model uses a large set of student- and school-level characteristics to identify the extent to which schools contribute to student achievement outcomes. In particular, a school-level value-added model was designed to accommodate the purpose of the value-added model, which was to help identify the top and bottom two high schools in school effectiveness for observation. This technical report describes the value-added model used by NCSU and developed in association with the Value-Added Research Center of the Wisconsin Center for Education Research at the University of Wisconsin-Madison. The report is divided into four parts: (1) description of the datasets used to produce the value-added estimates; (2) model specifications used to estimate value added for high schools in FWISD; (3) analysis of the value-added results; and (4) selection of high and low value-added schools for qualitative study. An appendix contains information on the following: (1) School Type; (2) Demographic Variables; (3) Grade Promotion; and (4) Test Scores. [For the full report, "Reaching for Rigor: Identifying Practices of Effective High Schools. Research Report," see ED561267.]