Shrinkage had no statistically significant effect on the relative probability that teachers of hard-to-predict students received consequences¶
Claim · All claims
Evidence · 1 study · causalr?·q2
Currency · newest study 2016 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2019: tool and model accuracy changes quickly
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? In the study sample, shrinkage did not significantly change the relative probability that teachers of hard-to-predict students received consequences. → Mariesa Herrmann 2016
Evidence¶
Mariesa Herrmann 2016¶
Mariesa Herrmann, Elias Walsh, Eric Isenberg. (2016). Shrinkage of Value-Added Estimates and Characteristics of Students with Hard-to-Predict Achievement Levels. Statistics and Public Policy, vol. 3, issue 1. https://www.mathematica.org/publications/ja-shrinkage-of-valueadded-estimates-and-characteristics-of-students-with-hardtopredict
q2 · i? · causal · r?
The article reports that "in our sample, shrinkage had no statistically significant effect on the relative probability that teachers of hard-to-predict students received consequences"; no effect size is printed, so the null is reported without one.
"However, in our sample, shrinkage had no statistically significant effect on the relative probability that teachers of hard-to-predict students received consequences."
Discussion¶
Related Claims¶
- Shrinkage could differentially affect consequences for teachers of fewer students or students with hard-to-predict achievement — related
- Teachers of students with hard-to-predict achievement levels tend to have less precise value-added estimates than teachers of other students — related
- Empirical Bayes shrinkage increases the precision of value-added estimates and reduces their absolute value for teachers of hard-to-predict students — related
- Shrinkage does not change accountability consequences for teachers of hard-to-predict students, since extreme-rating probabilities are unaffected — possibly the same claim (merge candidate)
- Shrinkage has no statistically significant effect on the relative probability that teachers of hard-to-predict students receive extreme value-added ratings — related
- Empirical Bayes shrinkage could be used to address bias in proxy pre-test value-added estimates — related
- Teachers of students with low prior achievement and who receive free lunch tend to have less precise value-added estimates — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
shrinkage-no-significant-effect-consequences-hard-to-predict |
title |
Shrinkage had no statistically significant effect on the relative probability that teachers of hard-to-predict students received consequences |
description |
Shrinkage had no statistically significant effect on the relative probability that teachers of hard-to-predict students received consequences |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2016 |
recheck_by |
2019 |
generated |
by process:wiki-ingest on 2026-10-08 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — mariesa-herrmann-2016 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.