ABSTRACT

In ophthalmologic or otolaryngologic studies, bilateral correlated data often arise when observations involving paired organs (e.g., eyes, ears) are measured from each subject. Based on Donner's model , in this paper, we focus on investigating the relationship between the disease probability and covariates (such as ages, weights, gender, and so on) via the logistic regression for the analysis of bilateral correlated data. We first propose a new minorization–maximization (MM) algorithm and a fast quadratic lower bound (QLB) algorithm to calculate the maximum likelihood estimates of the vector of regression coefficients, and then develop three large-sample tests (i.e., the likelihood ratio test, Wald test, and score test) to test if covariates have a significant impact on the disease probability. Simulation studies are conducted to evaluate the performance of the proposed fast QLB algorithm and three testing methods. A real ophthalmologic data set in Iran is used to illustrate the proposed methods.

摘要

在眼科或耳鼻喉科研究中，当从每个受试者测量涉及成对器官（例如，眼睛、耳朵）的观察时，通常会出现双边相关数据。在Donner模型的基础上，本文重点研究疾病概率与协变量（如年龄、体重、性别等）之间的关系，通过逻辑回归分析双边相关数据。我们首先提出了一种新的最小化-最大化(MM) 算法和一个快速二次下界(QLB) 算法计算回归系数向量的最大似然估计，然后开发三个大样本检验（即似然比检验、Wald 检验和分数检验）来检验协变量是否对回归系数有显着影响。疾病概率。进行仿真研究以评估所提出的快速 QLB 算法和三种测试方法的性能。伊朗的真实眼科数据集用于说明所提出的方法。