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功效分析与零假设显著性检验。

Power Analysis for Null Hypothesis Significance Testing.

机构信息

Department of Orthopeadic Surgery, The Rothman Institute, Thomas Jefferson University Hospital, Philadelphia, PA.

出版信息

Clin Spine Surg. 2021 Mar 1;34(2):63-65. doi: 10.1097/BSD.0000000000001079.

Abstract

Before conducting a scientific study, a power analysis is performed to determine the sample size required to test an effect within allowable probabilities of Type I error (α) or Type II error (β). The power of a study is related to Type II error by 1-β. Most scientific studies set α=0.05 and power=0.80 as minimums. More conservative study designs will decrease α or increase power, which will require a larger sample size. The third and final parameter required for a power analysis is the effect size (ES). ES is a measure of the strength of the observation in the outcome of interest (ie, the dependent variable). ES must be estimated from pilot studies or published values. A small ES will require a larger sample size than a large ES. It is possible to detect statistically significant findings even for very small ES, if the sample size is sufficiently large. Therefore, it is also essential to evaluate whether ES is sufficiently large to be clinically meaningful.

摘要

在进行科学研究之前,需要进行功效分析,以确定在可接受的Ⅰ类错误(α)或Ⅱ类错误(β)概率内测试效果所需的样本量。研究的功效与Ⅱ类错误呈反比关系,即 1-β。大多数科学研究将α=0.05 和功效=0.80 作为最低标准。更保守的研究设计将降低α或提高功效,这将需要更大的样本量。功效分析所需的第三个也是最后一个参数是效应大小(ES)。ES 是对感兴趣的结果(即因变量)中观察结果的强度的度量。ES 必须根据初步研究或已发表的值进行估计。较小的 ES 需要比较大的 ES 更大的样本量。如果样本量足够大,即使 ES 非常小,也有可能检测到具有统计学意义的发现。因此,评估 ES 是否足够大以具有临床意义也很重要。

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