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Wrangling with p-values versus effect sizes to improve medical decision-making: A tutorial.
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Wrangling with p-values versus effect sizes to improve medical decision-making: A tutorial. The International journal of eating disorders Kraemer, H. C., Neri, E. n., Spiegel, D. n. 2020Abstract
The most pervasive and damaging myth in clinical ÌÇÐÄ´«Ã½ is that the smaller the p-value, the stronger the hypothesis. In reality, the p-value primarily reflects the quality of ÌÇÐÄ´«Ã½ design decisions. The most common proposal to avoid misleading conclusions from clinical ÌÇÐÄ´«Ã½ requires the appropriate use of effect sizes, but which effect size, used when and how, is an open question. A solution is proposed for perhaps the most common problem in clinical ÌÇÐÄ´«Ã½, the comparison between two populations, for example, comparison of two treatments in a randomized clinical trial or comparison of high risk versus low risk individuals in an epidemiological study: the success rate difference or equivalently the number needed to treat/take (NNT).
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