Murdoch I E, Morris S S, Cousens S N
Department of Preventive Ophthalmology, Institute of Ophthalmology, London.
Br J Ophthalmol. 1998 Aug;82(8):971-3. doi: 10.1136/bjo.82.8.971.
In conclusion, when an observation by its nature involves two eyes, as for blindness, statistical analyses should be conducted on individuals rather than eyes and between eye correlation is not a problem. In other circumstances, if information on only one eye per individual is used in the analysis there is a potential "waste" of information leading to less precise estimates of effect and less power. In addition, bias may be introduced into a study if there is non-random selection of the eye for inclusion in the analysis. The use of an overall summary of ocular findings for an individual may result in "wastage" of information in a similar fashion to the use of only one eye per individual. On the other hand, an analysis of individual eyes with no allowance made for between eye correlation may result in falsely narrow confidence intervals around estimates of effect. Between eyes correlation may be assessed empirically using the kappa statistic or similar means. If between eye correlation is substantial, statistical techniques exist which can utilise all available data while allowing for the correlation. In some circumstances a powerful design may be to use the fellow eye as a "control". Two conclusions may be drawn from this review of analytical approaches to the analysis of clinical data in the BJO. Firstly, the analytical approaches employed in many studies fail to use all the data available. In other words the analysis is less than "optimal". Secondly, in a proportion of studies, inappropriate statistical methods are used which may lead the investigator to draw inappropriate conclusions. In other words, the analysis is invalid. Ophthalmic data, by their very nature, present particular statistical challenges. We emphasise the need to involve appropriate statistical expertise in the design and analysis of ophthalmic studies.
总之,当一项观察按其性质涉及双眼时,如失明情况,统计分析应针对个体而非眼睛进行,且两眼之间的相关性不成问题。在其他情况下,如果分析中仅使用个体单眼的信息,则可能存在信息“浪费”,导致效应估计不够精确且检验效能降低。此外,如果纳入分析的眼睛选择不随机,可能会在研究中引入偏差。使用个体眼部检查结果的总体汇总可能会以与仅使用个体单眼信息类似的方式导致信息“浪费”。另一方面,对个体眼睛进行分析而不考虑两眼之间的相关性,可能会导致效应估计的置信区间错误地变窄。两眼之间的相关性可以使用kappa统计量或类似方法进行实证评估。如果两眼之间的相关性很强,则存在一些统计技术可以在考虑相关性的同时利用所有可用数据。在某些情况下,一种有效的设计可能是将对侧眼用作“对照”。从对《英国眼科杂志》临床数据分析方法的综述中可以得出两个结论。首先,许多研究中采用的分析方法未能使用所有可用数据。换句话说,分析并非“最优”。其次,在一定比例的研究中,使用了不适当的统计方法,这可能导致研究者得出不适当的结论。换句话说,分析是无效的。眼科数据因其本质特性带来了特殊的统计挑战。我们强调在眼科研究的设计和分析中需要有适当的统计专业知识参与。