Documentation

Data Sources and Methodology

Last updated: January 2026

MEDE Methodology Overview

The Missouri Education Data Explorer (MEDE) integrates multiple authoritative data sources to provide a coherent, transparent, and comparable view of student outcomes across Missouri. The methodology is designed to balance analytical rigor with clarity, ensuring that results are interpretable by educators, policymakers, and community stakeholders while remaining faithful to the underlying data and its limitations. All indicators are documented with explicit source attribution, consistent definitions, and clear handling of missing or suppressed data.


Data Sources

MEDE draws on three primary sources. National Assessment of Educational Progress (NAEP) provides an external benchmark of student achievement in reading and mathematics, allowing Missouri trends and subgroup performance to be contextualized against national performance over time. NAEP data are used for statewide context and trend validation rather than for fine-grained local comparisons.


State-level administrative data come from the Missouri Department of Elementary and Secondary Education (DESE) via the Missouri Comprehensive Data System (MCDS). These data include enrollment, demographics, assessment proficiency, growth, attendance, and other K–12 indicators at the school, district, county, and state levels. MCDS serves as the authoritative source for Missouri’s standardized test results, growth measures, and accountability-related metrics used throughout MEDE.


Postsecondary and workforce outcomes are sourced from the Missouri Department of Higher Education and Workforce Development (DHEWD), specifically Tables 1–3. These tables provide information on high school graduates’ postsecondary enrollment, persistence, and workforce participation, enabling MEDE to link K–12 outcomes with early postsecondary and labor market indicators where available. Together, these sources allow MEDE to present a longitudinal view of educational pathways while respecting differences in scope, coverage, and reporting rules across agencies.


Growth Scores and Percentile Ranks

School-level academic growth is reported by DESE as standardized (z-score) measures that indicate how much students’ progress differs from the statewide average, after accounting for prior achievement. To make these growth results more intuitive and comparable across contexts, MEDE converts growth z-scores into percentile ranks. This conversion is done by mapping each z-score to its corresponding percentile in the standard normal distribution (or, where specified, the empirical statewide distribution for that year and grade span). The resulting percentile rank answers a straightforward question: how did this school’s growth compare to other Missouri schools? A percentile of 75, for example, indicates that a school’s growth exceeded that of roughly three-quarters of schools statewide.


Aggregation and Missing-Data Accounting

When aggregating assessment results from schools to districts, counties, or regions, MEDE explicitly tracks the completeness of the underlying data. Missouri suppresses certain cell counts—often at the school or subgroup level—to protect student privacy, which can result in some students not being represented in one or more performance levels (Below Basic, Basic, Proficient, Advanced) in published tables. For each aggregation, MEDE calculates the percent of scores missing by comparing the sum of students represented in the reported performance levels to the total tested enrollment for that geography and year. Any shortfall is attributed to suppressed or unreported counts and is expressed as a percentage of the total.


This missing-data percentage is displayed alongside aggregated results to provide essential context. It allows users to assess the reliability and completeness of comparisons across places and over time, particularly when examining smaller geographies or subgroups where suppression is more common. By surfacing both outcomes and data coverage, MEDE ensures that users can interpret patterns responsibly and understand where caution is warranted.