Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for individual students and groups of students. Monitoring student progress is central to accountability systems in general and is useful for measuring how well students respond to instruction or intervention. Progress monitoring entails tracking individual growth across the academic year. Thus, it is important to understand why individual students differ on an outcome beyond what can be known by accounting for performance on a status assessment. This study examines the relations among descriptive measures of growth (simple difference and average difference) and inferential measures (ordinary least squares and empirical Bayes) for students in grades 3-10 and considers how well such measures statistically explain differences in end-of-year reading comprehension after controlling for student performance on a mid-year status assessment. The study also looks at how the results change when controlling for initial (fall) and final (spring) status and when the relations among individual growth curves, status, and end-of-year reading comprehension performance depend on end-of-year reading comprehension performance. [For the full report, see ED544678.]