English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In a meta-analysis of intervention or group comparison studies, researchers often encounter the circumstance in which the standardized mean differences (d-effect sizes) are computed at multiple levels (e.g., individual vs. cluster). Cluster-level d-effect sizes may be inflated and, thus, may need to be corrected using the intraclass correlation (ICC) before being combined with individual-level d-effect sizes. The ICC value, however, is seldom reported in primary studies and, thus, may need to be computed from other sources. This article proposes a method for estimating the ICC value from the reported standard deviations within a particular meta-analysis (i.e., estimated ICC) when an appropriate default ICC value (Hedges, 2009b) is unavailable. A series of simulations provided evidence that the proposed method yields an accurate and precise estimated ICC value, which can then be used for correct estimation of a d-effect size. The effects of other pertinent factors (e.g., number of studies) were also examined, followed by discussion of related limitations and future research in this area.

Use of the estimated intraclass correlation for correcting differences in effect size by level