Claims

Effect-size heterogeneity across Covid-19 studies is essentially total (I2 = 100%), justifying a random-effects model

Claim · All claims
Evidence · 1 study · quant-synthesis r3 · 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? All variability in effect-size estimates is due to heterogeneity rather than sampling error (I2 = 100%; τ2 = 1.74). → Di Pietro Giorgio 2023

Evidence

Di Pietro Giorgio 2023

Di Pietro Giorgio. (2023). The impact of Covid-19 on student achievement: Evidence from a recent meta-analysis. Educational Research Review. https://doi.org/10.1016/j.edurev.2023.100530

q3 · i? · quant-synthesis · r3

Heterogeneity assessment in the meta-analysis of 239 estimates: I2 has a value of 100% and between-study variance τ2 is 1.74, corroborating substantial heterogeneity and the choice of the random-effects model.

"This suggests that all the variability in the effect-size estimates is due to heterogeneity as opposed to sampling error."

Discussion

Page metadata
Field Value
type claim
id covid-meta-analysis-total-heterogeneity-i2-100
title Effect-size heterogeneity across Covid-19 studies is essentially total (I2 = 100%), justifying a random-effects model
description Effect-size heterogeneity across Covid-19 studies is essentially total (I2 = 100%), justifying a random-effects model
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 — di-pietro-giorgio-2023

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