Oregon School Data Explorer

Statistical reports and source scripts

A reader-friendly synthesis of the numeric analyses behind the Evidence Lab findings, followed by grouped links to detailed reports, source scripts, figures, and machine-readable outputs.

Scope reminder: the primary models use one official 2024-25 all-tested-grades row for each ordinary elementary school site. Results are weighted by scored students. Middle-school results are separate sensitivities; high and combined-grade sites are excluded from the primary tract-SES interpretation. These are school-level associations and predictive checks, not causal estimates.
At a glance
  • The strongest recurring school-level associations involve student poverty concentration, attendance, and local adult BA+ levels.
  • Income remains correlated with outcomes, but adds comparatively little after adult BA+, attendance, and student poverty.
  • ODE Students Experiencing Poverty is the strongest enrolled-student hardship measure in the audited elementary specifications.
  • Spending/class-size effects are weaker and less stable in statewide cross-sectional models.
  • The adult-education-over-income ordering remains stable across repeated elementary half-sample checks.
Model setup
  • Primary unit: one official Total Population All Grades row per ordinary elementary school.
  • Weights: Scored Performance Denominator for 2024-25 achievement models.
  • Attendance must match the assessment population; censored or unavailable rates are omitted without midpoint or whole-school substitution.
  • Main outcome: Percent Proficient.
  • Income companion spec: income, adult BA+ rate, attendance.
  • Companion 2024-25 spec: poverty, adult BA+ rate, attendance (with optional income add-back).
  • Exploratory predictors: overall spending per student, classroom spending per student, median class size.
Joint model results by subject

Elementary-primary income spec: Percent Proficient ~ income + adult BA+ + attendance

Subject Beta income Beta education Beta attendance R^2
English (ELA) 0.065 0.455 0.438 0.684
Math 0.088 0.430 0.446 0.687
Science 0.110 0.487 0.290 0.571

These are standardized in-sample coefficients. The companion report separately gives repeated held-out R^2 and full coverage diagnostics.

Poverty-aware companion checks (2024-25)

In ordinary-school cross-validated tests, replacing income with Students Experiencing Poverty materially improved fit in all three subjects.

  • ELA mean repeated-CV R^2: 0.6767 (income) vs 0.7676 (poverty); with both: 0.7727.
  • Math mean repeated-CV R^2: 0.6788 (income) vs 0.7475 (poverty); with both: 0.7485.
  • Science mean repeated-CV R^2: 0.5636 (income) vs 0.6538 (poverty); with both: 0.6546.

Interpretation: poverty predicts held-out school results better in these elementary-primary specifications, while income remains useful neighborhood description. SEP interval endpoint and exact-only checks preserve the ordering.

Interaction effects

Paired held-out tests replace the old, mechanically optimistic in-sample interaction comparison. The clearest gain appears in Math; the evidence is weaker or inconsistent in ELA and Science.

  • ELA: mean held-out Delta R^2 = +0.005 (income model) and approximately 0.000 (poverty model).
  • Math: mean held-out Delta R^2 = +0.016 (income model) and +0.012 (poverty model).
  • Science: mean held-out Delta R^2 = approximately 0.000 (income model) and +0.004 (poverty model), with principal repeat ranges including zero.
Outcome-level heterogeneity

In the statewide Math Percent Level 4 income-and-adult-education model, the standardized adult-education association was stronger than the income association (beta 0.534 versus 0.132; R^2 = 0.399).

Spending and class size

Spending variables are highly collinear with each other and with other SES measures. Ridge and permutation-based checks showed model-sensitive contributions: usually secondary in pooled models, but more prominent in several fixed-effects specifications. Median class size remained near-zero after controls.

Robustness
  • Repeated elementary half-sample checks preserve adult BA+ > income ordering.
  • 2024-25 poverty-aware checks preserve a meaningful BA+ association while showing that school poverty is also a first-tier predictor.
  • SEP midpoint, endpoint, and exact-only checks preserve the principal model ordering.
  • Historical comparisons are deferred pending a separate historical-data audit.
Responsible interpretation
  • These are association models, not causal estimates.
  • School-level aggregation can hide within-school heterogeneity.
  • School-site tracts may represent elementary catchments imperfectly and are weaker proxies for wider-drawing schools.
  • Repeated-split ranges are descriptive stability checks, not confidence intervals.
  • Non-core model families need their own audit before their older claims are treated as current.

Report and script index

Reports are grouped with the source files or machine-readable outputs that produced them. The companion full-text exports are included where they are useful for auditing.