REGRESSION MODELS FOR ANALYSIS OF OPHTHALMOLOGICAL DATA

描述(研究人员摘要)：在一些眼科研究中， 眼睛状况的严重程度是根据有序的分类进行分级的 比例。例如，在一项关于糖尿病视网膜病变的研究中，眼睛被分级为 以下有序类别之一；无状况、中等、严重、 而且具有增殖性。这项提案的目标是实现 有助于提高我们的分析和分析能力的统计研究 解读这些来自眼科研究的有序分类数据。 首先，研究人员建议开发一类通用的回归 分析单变量有序分类数据的模型。其次， 研究人员建议开发一种非常普遍的双变量概率回归 眼科特殊协变量结构的调整模型 数据。这将使二元有序分类数据的建模变得容易 源于一些眼科研究。第三，调查人员 提出了基于全局关联的对数线性关联模型的推广 和局部交叉乘积比率，以便它们可以用于分析 来自眼科研究的数据。最后，调查人员 建议研究使用广义估计法的可行性 眼科资料分析中的方程式方法 需要对相关结构进行假设 左眼和右眼之间。

DESCRIPTION (Investigator's Abstract): In some ophthalmology studies, severity of an eye condition is graded according to an ordered categorical scale. For example, in a study of diabetic retinopathy, eyes are graded as one of the following ordered categories; no condition, moderate, severe, and proliferative. The objectives of this proposal are to carry out statistical research that will help improve our ability to analyze and interpret such ordered categorical data arising from ophthalmology studies. Firstly, the investigators propose to develop a general class of regression models for analyzing univariate ordered categorical data. Secondly, the investigators propose to develop a very general bivariate probit regression model to adjust for specific covariate structure in the ophthalmological data. This will allow easy modeling of bivariate ordered categorical data arising from some ophthalmology studies. Thirdly, the investigators propose to generalize the log-linear association models based on the global and the local cross-product ratio so that they can be used in analyzing data arising from ophthalmologic studies. Finally, the investigators propose to investigate the feasibility of using the generalized estimating equation approach in the analysis of ophthalmologic data in which no assumptions are needed to be made regarding the correlation structure between the left and right eyes.