User's guide to correlation coefficients
By Haldun Akoglu. Turkish Journal of Emergency Medicine, 2018
4,943 citations recorded by the source corpus.
When writing a manuscript, we often use words such as perfect, strong, good or weak to name the strength of the relationship between variables. However, it is unclear where a good relationship turns into a strong one. The same strength of r is named differently by several researchers. Therefore, there is an absolute necessity to explicitly report the strength and direction of r while reporting correlation coefficients in manuscripts. This article aims to familiarize medical readers with several different correlation coefficients reported in medical manuscripts, clarify confounding aspects and summarize the naming practices for the strength of correlation coefficients.
Subfields: Artificial Intelligence, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/dd7ceee5b05eb672e850140220f7db44ead3968f
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Citations in the corpus
- DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers (2022, background): “25) indicates ‘very strong’ correlation between two evaluations [2].”
- DALL-EVAL: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models (2022, background): “We find a ‘very strong’ [2] correlation (φ = 0.”
- Bland-Altman analysis: A paradigm to understand correlation and agreement (2018, methodology): “001), which indicates a very strong relationship between the variables.(5) Does this mean that we can use a given variable instead of the other? Can we replace a laboratory method with the new one, regarding this strong relationship? This argument is not always correct.”
- Immediate Psychological Effects of the COVID-19 Quarantine in Youth From Italy and Spain (2020, methodology): “05, weak; and >0, none or very weak (Akoglu, 2018).”