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临床人类视觉研究的统计学指南。

Statistical guidelines for clinical studies of human vision.

机构信息

Ophthalmic Research Group, School of Life and Health Sciences, Aston University, Birmingham, UK.

出版信息

Ophthalmic Physiol Opt. 2011 Mar;31(2):123-36. doi: 10.1111/j.1475-1313.2010.00815.x.

Abstract

Statistical analysis of data can be complex and different statisticians may disagree as to the correct approach leading to conflict between authors, editors, and reviewers. The objective of this article is to provide some statistical advice for contributors to optometric and ophthalmic journals, to provide advice specifically relevant to clinical studies of human vision, and to recommend statistical analyses that could be used in a variety of circumstances. In submitting an article, in which quantitative data are reported, authors should describe clearly the statistical procedures that they have used and to justify each stage of the analysis. This is especially important if more complex or 'non-standard' analyses have been carried out. The article begins with some general comments relating to data analysis concerning sample size and 'power', hypothesis testing, parametric and non-parametric variables, 'bootstrap methods', one and two-tail testing, and the Bonferroni correction. More specific advice is then given with reference to particular statistical procedures that can be used on a variety of types of data. Where relevant, examples of correct statistical practice are given with reference to recently published articles in the optometric and ophthalmic literature.

摘要

数据的统计分析可能很复杂,不同的统计学家可能对正确的方法有不同的看法,这导致了作者、编辑和审稿人之间的冲突。本文的目的是为眼视光学期刊的投稿者提供一些统计建议,提供专门针对人类视觉临床研究的建议,并推荐在各种情况下可以使用的统计分析方法。在提交报告定量数据的文章时,作者应清楚描述他们所使用的统计程序,并证明分析的每一个阶段都是合理的。如果进行了更复杂或“非标准”的分析,这一点尤其重要。本文首先讨论了一些与样本量和“功效”、假设检验、参数和非参数变量、“自举方法”、单尾和双尾检验以及 Bonferroni 校正有关的数据分析的一般评论。然后,根据各种类型的数据可以使用的特定统计程序提供更具体的建议。在相关情况下,还参考最近发表在眼视光学文献中的文章,给出了正确的统计实践的示例。

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