Testing the Magnitude of Correlations Across Experimental Conditions
Simone Di Plinio · 2022 · Frontiers in Psychology
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
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
Abstract by Simone Di Plinio, Frontiers in Psychology (2022) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3389/fpsyg.2022.860213