Graduation and dropout rates are difficult to calculate. These difficulties arise because of both conceptual ambiguities and imperfect data. In this paper, the authors review some of these challenges, discuss how the challenges have been approached when using cross-sectional data, and describe a method that analyzes longitudinal, student-level data to provide an improved estimate of graduation and dropout rates. They then apply that method to estimate graduation and dropout rates for the Pittsburgh Public Schools district-wide and for each high school in the district.
This report was prepared for the Pittsburgh Public Schools and was conducted by RAND Education.
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