ACCOUNTING FOR THE CORRELATION BETWEEN FELLOW EYES IN REGRESSION-ANALYSIS

ACCOUNTING FOR THE CORRELATION BETWEEN FELLOW EYES IN REGRESSION-ANALYSIS
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DOI:
10.1001/archopht.1992.01080150079033
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发表时间:
1992-03-01
影响因子:
--
通讯作者:
ROSNER, B
ROSNER, B
中科院分区:
其他
文献类型:
--
作者:
GLYNN, RJ;ROSNER, B

文献摘要

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适当使用所有可用眼睛的回归技术在眼科文献中很少被应用,尽管在统计模型的开发和计算机软件的可用性方面都取得了进展以适应这些模型。我们考虑了Rosner的一般线性模型和多点Logistic回归方法,以及梁和Zeger的估计方程方法,分别应用于线性回归和Logistic回归。方法使用两个真实的数据集:(1)视网膜色素变性患者的视力损害和(2)青光眼评估的老年患者的总体视野损害。我们讨论了这些模型对系数的解释,以及这些方法与其他方法相比的优势,如以个体而不是眼睛作为分析单位,对右眼和左眼进行单独的回归分析,或使用普通回归技术而不考虑双眼之间的相关性。具体的优势包括增强的统计能力、更易解释的回归系数、更高的估计精度以及对某些眼睛丢失数据的较低敏感度。我们的结论是,这些模型应该在眼科研究中更频繁地使用,我们为选择其他模型提供了指南。
Regression techniques that appropriately use all available eyes have infrequently been applied in the ophthalmologic literature, despite advances both in the development of statistical models and in the availability of computer software to fit these models. We considered the general linear model and polychotomous logistic regression approaches of Rosner and the estimating equation approach of Liang and Zeger, applied to both linear and logistic regression. Methods were illustrated with the use of two real data sets: (1) impairment of visual acuity in patients with retinitis pigmentosa and (2) overall visual field impairment in elderly patients evaluated for glaucoma. We discuss the interpretation of coefficients from these models and the advantages of these approaches compared with alternative approaches, such as treating individuals rather than eyes as the unit of analysis, separate regression analyses of right and left eyes, or utilization of ordinary regression techniques without accounting for the correlation between fellow eyes. Specific advantages include enhanced statistical power, more interpretable regression coefficients, greater precision of estimation, and less sensitivity to missing data for some eyes. We concluded that these models should be used more frequently in ophthalmologic research, and we provide guidelines for choosing between alternative models.