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Abstract：
Myopia is a global healthcare concern and effective analyses of dioptric power are important in evaluating potential treatments involving surgery, orthokeratology, drugs such as low-dose (0.05%) atropine and gene therapy. This paper considers issues of concern when analysing refractive state such as data normality, transformations, outliers and anisometropia. A brief review of methods for analysing and representing dioptric power is included but the emphasis is on the optimal approach to understanding refractive state (and its variation) in addressing pertinent clinical and research questions. Although there have been significant improvements in the analysis of refractive state, areas for critical consideration remain and the use of power matrices as opposed to power vectors is one such area. Another is effective identification of outliers in refractive data. The type of multivariate distribution present with samples of dioptric power is often not considered. Similarly, transformations of samples (of dioptric power) towards normality and the effects of such transformations are not thoroughly explored. These areas (outliers, normality and transformations) need further investigation for greater efficacy and proper inferences regarding refractive error. Although power vectors are better known, power matrices are accentuated herein due to potential advantages for statistical analyses of dioptric power such as greater simplicity, completeness, and improved facility for quantitative and graphical representation of refractive state.
摘要：
近视是全球医疗保健关注的问题，有效的屈光度分析对于评估涉及手术的潜在治疗方法非常重要。角膜塑形术,药物如低剂量（0.05％）阿托品和基因治疗。本文考虑了分析屈光状态时需要关注的问题，如数据正态，转换，异常值和屈光参差。包括分析和表示屈光度的方法的简要回顾，但重点是在解决相关临床和研究问题时理解屈光状态（及其变化）的最佳方法。虽然屈光状态的分析有了显著的改进，关键考虑的领域仍然存在，使用功率矩阵而不是功率向量就是这样一个领域。另一个是有效识别屈光数据中的异常值。通常不考虑屈光度样本中存在的多变量分布类型。同样，样品（屈光度）向正态的转换以及这种转换的影响尚未得到彻底的探索。这些区域(异常值，正常和转换）需要进一步研究，以获得更大的疗效和有关屈光不正的正确推论。虽然功率矢量是众所周知的，由于屈光度统计分析的潜在优势，例如更简单，完整性，并改进了屈光状态的定量和图形表示的设施。
