ArticleFrontiers in psychology2022
Testing the Magnitude of Correlations Across Experimental Conditions.
Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Black-White Differences Related to Ageism and Health: Evidence from the Experiences of Aging in Society Project.Journal of racial and ethnic health disparities · 2026Article
- Mapping Lesion-Related Human Aggression to a Common Brain Network.Biological psychiatry · 2025Article
- Untangling discrepancies between cerebrovascular autoregulation correlation coefficients: An exploration of filters, coherence and power.Physiological reports · 2025Article
- Validation of the Italian Sense of Agency Scale and Its Relevance to Well-Being: An Iterative Bootstrap Approach.Behavioral sciences (Basel, Switzerland) · 2024Article
- Article
- EEG-derived brain graphs are reliable measures for exploring exercise-induced changes in brain networks.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Correlation coefficients are often compared to investigate data across multiple research fields, as they allow investigators to determine different degrees of correlation to independent variables. Even with adequate sample size, such differences may be minor but still scientifically relevant. To date, although much effort has gone into developing methods for estimating differences across correlation coefficients, adequate tools for variable sample sizes and correlational strengths have yet to be tested. The present study evaluated four different methods for detecting the difference between two correlations and tested the adequacy of each method using simulations with multiple data structures. The methods tested were Cohen's q, Fisher's method, linear mixed-effects models (LMEM), and an
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.