Measurement error bias inflates peer spillover effects while attenuating the BFLPE; controls strengthen the BFLPE and weaken the spillover effect¶
Claim · All claims
Evidence · 1 study · associationalr3·q3
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person
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.
q3 i? Failing to control for measurement error produced artefactual peer spillover effects, and both facets of student-level under-specification made BFLPEs less negative while they remained statistically significant. → Televantou 2023
Evidence¶
Televantou 2023¶
Televantou, I., Marsh, H. W., Xu, K. M., Guo, J., & Dicke, T. (2023). Peer Spillover and Big-Fish-Little-Pond Effects with SIMS80: Revisiting a Historical Database Through the Lens of a Modern Methodological Perspective. Educational Psychology Review. https://doi.org/10.1007/s10648-023-09816-3
q3 · i? · associational · r3
Comparison of doubly manifest versus doubly latent model estimates across the three countries in Table 3 shows the peer spillover effect was largest in doubly manifest models (e.g., .808 for the USA) and shrank under doubly latent models, indicating "artefactual peer spillover effects" from uncontrolled measurement error.
"failing to control for measurement error led to artefactual peer spillover effects. Controlling for measurement error alone only partially corrected for the positive bias in the peer spillover effect"
Discussion¶
Related Claims¶
- The Big-Fish-Little-Pond effect on mathematics self-concept is negative and statistically significant in all three countries under a fully specified doubly latent model — related
- Positive class-level peer spillover effects on mathematics achievement fail to replicate once measurement error is controlled with doubly latent models — a narrower finding that bears on this claim
- A low alpha for an error-prone covariate can attenuate, inflate, or artificially produce a spurious effect (phantom effect) in the coefficient of a perfectly reliable predictor — a broader claim this one bears on
- When compositional effects are constrained equal across countries, the overall peer spillover effect is negative and non-significant while the BFLPE remains negative and significant — related
- Contextual-mean effects show little moderation by individual achievement; apparent positive moderation is illusory when the quadratic term is omitted — related
- Positive school-average achievement effects on subsequent achievement can be phantom effects that disappear under doubly-latent modeling with covariates — related
- Doubly latent multilevel structural equation models disaggregate disciplinary-problem effects at student versus classroom level — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
measurement-error-bias-compositional-effects |
title |
Measurement error bias inflates peer spillover effects while attenuating the BFLPE; controls strengthen the BFLPE and weaken the spillover effect |
description |
Measurement error bias inflates peer spillover effects while attenuating the BFLPE; controls strengthen the BFLPE and weaken the spillover effect |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2023 |
generated |
by process:wiki-ingest on 2026-10-21 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — televantou-2023 |
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