Wednesday March 6, 12:00 PM - 4:00 PM
Workshop C
Using School-Level Data from the Stanford Education Data Archive
Sean Reardon, Stanford University
Andrew D. Ho, Harvard University
Benjamin R. Shear, University of Colorado, Boulder
Erin M. Fahle, St. John’s University

The Stanford Education Data Archive (SEDA) is a publicly available dataset based on roughly 330 million standardized test scores from students in U.S. public schools. SEDA contains estimate of the average test scores for school districts, counties, and metropolitan statistical areas by grade (grades 3-8), year (2009-2016), subject (math and reading/language arts), and subgroup (gender, race/ethnicity, and economic disadvantage). Scores from different states, grades, and years are linked to a common national scale, allowing comparisons of student performance over states and time.

In March 2019, SEDA will release average test scores for U.S. schools. This workshop will provide a description of SEDA’s contents and construction, focusing on the newly added school-level test score estimates and covariates. It will then include a description of the how to use the school-level data in descriptive and causal research, as well as a discussion of the strengths and limitations of the data. The workshop will include code, activities, and examples using Stata and R. Participants should bring a laptop with R or Stata, or be prepared to work from raw data using their preferred statistical program.

More information about SEDA is available at

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