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.
