In Clark County, One-Star designation significantly raises math and ELA scores for all students¶

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person · recheck by 2028: local conditions change quickly

Subclaims¶

q2 i? A regression discontinuity analysis found statistically significant jumps of 0.33 standard deviations in math and 0.29 standard deviations in ELA at the One-Star threshold for all Clark County students. → Tanner 2025

Evidence¶

Tanner 2025¶

Tanner, S., Krausen, K., Garcia, B., & Brown, A. (2025). Understanding the At-risk indicator: Nevada's Pupil-Centered Funding Plan. WestEd. https://eric.ed.gov/?id=ED677573

q2 · i? · causal · r2

RDD analysis restricted to Clark County School District, which the report says educates more than two thirds of the state's students including more than 80 percent of those designated At-risk. "There is a marked jump at the One-Star threshold of 0.33 standard deviations" in math, significant; ELA showed "the jump of 0.29 standard deviations at the One-Star threshold is statistically significant." The report prints these as threshold jumps in grade-standardized scores, not as d-type effect sizes, so impact is null.

"There is a marked jump at the One-Star threshold of 0.33 standard deviations. This effect is statistically significant, indicating that the resources flowing to One-Star schools in Clark County are having a substantial positive effect on students’ math scores."

Discussion¶

Related Claims¶

• For Clark County students designated At-risk, One-Star designation significantly raises math but not ELA scores — related
• Statewide, One-Star designation has a modest significant positive effect on ELA but not on math scores — related
• Regression discontinuity estimates show high internal validity, with average bias below 0.01 standard deviations relative to RCT estimates at the same cutoff — a broader claim this one bears on
• Regression discontinuity impact estimates for two education interventions were not significantly different from experimental impact estimates, though point-estimate differences were sometimes nontrivial — a broader claim this one bears on
• Statistical theory predicts that regression discontinuity provides valid causal inference at the cutoff score determining treatment assignment — a broader claim this one bears on
• Shrunken study-specific RD bias estimates stay below 0.07 standard deviations, indicating good external validity — a broader claim this one bears on
• Robust RDD methods protect against model misspecification but require much larger sample sizes to detect small effects — a broader claim this one bears on