Use Bayesian inference, equivalence testing, and multiple operationalizations to make null effects theoretically informative¶
Strategy · All strategies
Evidence · 4 claims (4 for) · 6 studies (3 theoretical, 2 causal, 1 review),q2–q3· 2 of 6 report an effect size · 3 claims rest on one study
Description¶
The article recommends methodological moves for treating nulls as informative rather than inconclusive. "Bayesian inference provides one avenue for quantifying evidence in favor of the null hypothesis," allowing researchers to distinguish absence of evidence from evidence of absence, and equivalence testing enables formal evaluation of whether effects are practically negligible. Including multiple operationalizations of ostensibly similar constructs strengthens inference, as convergent null effects provide more robust constraints than any single test.
Design Implications¶
Context¶
Requirements¶
- Analytical approaches that move beyond dichotomous significance testing, and inclusion of multiple operationalizations of ostensibly similar constructs within the same study
Constraints¶
Target Learners¶
- education researchers designing intervention studies
Target Learning Goals¶
- drawing valid inferences about cognitive invariance from null intervention results
Affordances¶
Claims¶
- Null Flanker effects under ecologically realistic exercise constrain claims of broad, generalized enhancement of executive control [+W]
- The immediate advantage of deep-processing prompts does not persist at a 5-month follow-up, with a Bayesian test confirming the null [+W]
- Media comparison studies produce uninterpretable "no significant difference" findings. [+M]
- No significant effect of order of phases on procedural knowledge in the Bayesian-reasoning replication [+W]
Related Strategies¶
Examples¶
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Key Sources¶
- David Moreau, Kristina Wiebels. (2026). Interventions as Probes of Cognitive Architecture: Commentary on Zhang et al. (2026). Educational Psychology Review. https://doi.org/10.1007/s10648-026-10150-7
Page metadata
| Field | Value |
|---|---|
type |
strategy |
id |
bayesian-equivalence-testing-for-null-effects |
title |
Use Bayesian inference, equivalence testing, and multiple operationalizations to make null effects theoretically informative |
description |
The article recommends methodological moves for treating nulls as informative rather than inconclusive. |
status |
review |
generated |
by process:wiki-ingest on 2026-10-21 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — david-moreau-2026 |
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