Interpreting Results from Statistical Hypothesis Testing: Understanding the Appropriate P-value.

Physical therapy research Pub Date : 2022-01-01 Epub Date: 2022-05-13 DOI:10.1298/ptr.R0019
Eiki Tsushima
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引用次数: 1

Abstract

Clinical research based on epidemiological study designs requires a good understanding of statistical analysis. This paper discusses the common misconceptions of p-values so that researchers and readers of research papers will be able to properly present and understand the results of null hypothesis significance testing (NHST). The p-values calculated by NHST are categorized as three different types: "significant at p <0.05," "significant at p <0.01," or "not significant." If specified, they may be written as p = 0.124. The 95% confidence interval (CI) of the supplementary statistics is presented regardless of the p-value, and the range of the CI is observed and discussed to determine whether the results are clinically valid. The effect size (ES), which is a measure of the magnitude of the effect, is also referenced and discussed. However, the ES should not be overestimated. It is important to examine the actual descriptive statistics and consider them comprehensively as much as possible. A high detection power of 80% or more indicates that NHST with high accuracy was applied. However, even when it falls below 80%, it is important to consider the limitations of the study, because the results are not completely useless.

Abstract Image

解释统计假设检验的结果:理解适当的p值。
基于流行病学研究设计的临床研究需要对统计分析有很好的理解。本文讨论了对p值的常见误解,以便研究人员和研究论文的读者能够正确地呈现和理解零假设显著性检验(NHST)的结果。NHST计算的p值分为三种不同的类型:“在p处显著
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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