Claims

The article presents a Bayesian reanalysis of NAEP long-term trend reading and math score changes from 2020 to 2023.

Claim · All claims
Evidence · 1 study · associational r? · q2
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person · recheck by 2028: baselines and conditions change

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? NAEP long-term trend reading and math score changes from 2020 to 2023 were reanalyzed using Bayesian methods. → Jennifer Starling 2023

Evidence

Jennifer Starling 2023

Jennifer Starling, Brian Gill. (2023). NAEP Long-Term Trend Reanalysis. Mathematica. https://www.mathematica.org/publications/naep-long-term-trend-reanalysis

q2 · i? · associational · r?

The publication's own abstract-level description states it is "A reanalysis of the National Assessment of Educational Progress (NAEP) long-term trend reading and math score changes from 2020 to 2023 using Bayesian methods." No effect sizes, sample details, or results are printed in the available text.

"A reanalysis of the National Assessment of Educational Progress (NAEP) long-term trend reading and math score changes from 2020 to 2023 using Bayesian methods."

Discussion

Page metadata
Field Value
type claim
id naep-ltt-2020-2023-bayesian-reanalysis
title The article presents a Bayesian reanalysis of NAEP long-term trend reading and math score changes from 2020 to 2023.
description The article presents a Bayesian reanalysis of NAEP long-term trend reading and math score changes from 2020 to 2023.
status review
evidence_strength weak
newest_evidence 2023
recheck_by 2028
generated by process:wiki-ingest on 2026-10-08
trust unverified — no one has confirmed this page's content
sources 1 — jennifer-starling-2023

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