Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego, La Jolla, California; Department of Ophthalmology, Federal University of São Paulo, São Paulo, Brazil.
Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego, La Jolla, California.
Ophthalmology. 2014 Jul;121(7):1317-21. doi: 10.1016/j.ophtha.2014.01.015. Epub 2014 Mar 5.
To identify the most commonly used statistical analyses in the ophthalmic literature and to determine the likely gain in comprehension of the literature that readers could expect if they were to add knowledge of more advanced techniques sequentially to their statistical repertoire.
Cross-sectional study.
All articles published from January 2012 through December 2012 in Ophthalmology, the American Journal of Ophthalmology, and Archives of Ophthalmology were reviewed. A total of 780 peer-reviewed articles were included. Two reviewers examined each article and assigned categories to each one depending on the type of statistical analyses used. Discrepancies between reviewers were resolved by consensus.
Total number and percentage of articles containing each category of statistical analysis were obtained. Additionally, we estimated the accumulated number and percentage of articles that a reader would be expected to be able to interpret depending on their statistical repertoire.
Readers with little or no statistical knowledge would be expected to be able to interpret the statistical methods presented in only 20.8% of articles. To understand more than half (51.4%) of the articles published, readers would be expected to be familiar with at least 15 different statistical methods. Knowledge of 21 categories of statistical methods was necessary to comprehend 70.9% of articles, whereas knowledge of more than 29 categories was necessary to comprehend more than 90% of articles. Articles related to retina and glaucoma subspecialties showed a tendency for using more complex analysis when compared with articles from the cornea subspecialty.
Readers of clinical journals in ophthalmology need to have substantial knowledge of statistical methodology to understand the results of studies published in the literature. The frequency of the use of complex statistical analyses also indicates that those involved in the editorial peer-review process must have sound statistical knowledge to appraise critically the articles submitted for publication. The results of this study could provide guidance to direct the statistical learning of clinical ophthalmologists, researchers, and educators involved in the design of courses for residents and medical students.
确定眼科文献中最常用的统计分析方法，并确定读者如果将更多高级技术的知识依次添加到其统计工具包中，他们对文献的理解可能会有何提高。
横断面研究。
回顾 2012 年 1 月至 12 月在《眼科学》《美国眼科学杂志》和《眼科学档案》上发表的所有同行评议文章。共纳入 780 篇同行评议文章。两名审查员检查了每篇文章，并根据使用的统计分析类型为每篇文章分配类别。审查员之间的分歧通过协商解决。
获得包含每种统计分析类别的文章总数和百分比。此外，我们还估计了读者根据其统计工具包能够解释的文章数量和百分比。
统计学知识很少或没有统计学知识的读者预计只能解释仅 20.8%的文章中呈现的统计方法。为了理解超过一半（51.4%）的文章，读者预计至少要熟悉 15 种不同的统计方法。要理解 70.9%的文章，需要掌握 21 类统计方法；而要理解超过 90%的文章，则需要掌握 29 类以上的统计方法。与角膜亚专业相关的文章相比，视网膜和青光眼亚专业的文章倾向于使用更复杂的分析。
眼科临床杂志的读者需要具备扎实的统计方法知识，才能理解文献中发表的研究结果。复杂统计分析的使用频率也表明，参与编辑同行评审过程的人员必须具备可靠的统计知识，才能批判性地评估提交发表的文章。本研究的结果可为指导临床眼科医生、研究人员和教育工作者提供指导，帮助他们为住院医师和医学生设计课程。
