When literatures are shaped by publication bias and small studies, meta‑analyses can exaggerate true effects more than a well‑designed single study. Funnel plots frequently show asymmetry, and simple corrections (e.g., trim‑and‑fill) substantially shrink pooled estimates. Trust should be weighted toward study quality and bias diagnostics, not the mere size of a literature.
— This warns policymakers and journalists against treating 'the literature says' as dispositive and pushes for bias‑aware evidence standards before adopting interventions.
Jerusalem Demsas
2026.01.15
78% relevant
Demsas cites how the microplastics literature and media syntheses portray risks despite methodological uncertainty and contamination concerns; that resonates with the existing point that pooled or literature‑level claims can exaggerate effects when the underlying studies are biased or underpowered (here Py‑GC/MS specificity and contamination).
Lee Jussim
2026.01.10
90% relevant
Jussim’s interview centers on a large meta‑analysis of audit studies that upends a widely held narrative about pervasive anti‑female hiring bias; this echoes the existing idea that pooled literatures can be misleading without bias diagnostics and robustness checks—exactly the methodological point Jussim emphasizes.
Josh Zlatkus
2026.01.07
78% relevant
The piece emphasizes that procedure, bias and selective publication produce misleading literatures—precisely the pathway by which meta‑analyses built on biased small studies overstate effects, a problem highlighted in the existing idea.
Tyler Cowen
2025.12.01
85% relevant
The article documents that after correcting for publication bias and assessing study quality (ROBINS‑E, GRADE), the apparent negative effect of inequality on mental health vanishes—concretely illustrating the existing idea that meta‑analytic findings can be inflated and need bias‑aware diagnostics.
2025.10.07
68% relevant
Jussim argues that a large share of peer‑reviewed psychology claims are false, foregrounding widespread non‑replication and propagation of unreplicable findings—echoing the critique that pooled literatures and selective methods can inflate effects and mislead policy.
2025.10.07
100% relevant
The article’s funnel plots and trim‑and‑fill re‑estimates for air‑pollution and mindfulness literatures that markedly reduce pooled effects.
2025.10.07
78% relevant
The article cites Maier et al. reporting that, after correcting publication bias, average nudge effects vanish, and a mega‑dataset from UK/US nudge units showing weaker impacts than published studies—classic signs that pooled literatures can inflate effect sizes.
2023.07.18
72% relevant
The article highlights how a body of biased, low‑quality or fabricated trials can distort pooled estimates; this maps to the existing point that meta‑analyses can exaggerate effects when underlying studies suffer from publication bias or fraud, with downstream policy consequences.
2015.01.04
62% relevant
The OSC findings illustrate a root cause (publication bias, QRPs) that can make pooled literature estimates optimistic; the paper provides concrete evidence why meta‑analytic estimates require bias diagnostics and not just pooled effect sizes.