Fast QLB algorithm and hypothesis tests in logistic model for ophthalmologic bilateral correlated data

Lin，Yi Qi1; Zhang，Yu Shun2; Tian，Guo Liang2; Ma，Chang Xing3

2020

10.1080/10543406.2020.1814794

Journal of Biopharmaceutical Statistics   影响因子和分区

1054-3406

1520-5711

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.

Assembly and decomposition technique bilateral correlated data fast QLB algorithm logistic regression model MM algorithm ophthalmologic study

SCI

英语

其他

National Natural Science Foundation of China[11771199]

Pharmacology & Pharmacy ; Mathematics

Pharmacology & Pharmacy ; Statistics & Probability

WOS:000574204400001

TAYLOR & FRANCIS INC

2-s2.0-85091945261

Scopus

1.Department of Statistics,The Chinese University of Hong Kong,Shatin,N.T,Hong Kong
2.Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen,China
3.Department of Biostatistics,The State University of New York at Buffalo,Buffalo,United States

Lin，Yi Qi,Zhang，Yu Shun,Tian，Guo Liang,et al. Fast QLB algorithm and hypothesis tests in logistic model for ophthalmologic bilateral correlated data[J]. Journal of Biopharmaceutical Statistics,2020.

Lin，Yi Qi,Zhang，Yu Shun,Tian，Guo Liang,&Ma，Chang Xing.(2020).Fast QLB algorithm and hypothesis tests in logistic model for ophthalmologic bilateral correlated data.Journal of Biopharmaceutical Statistics.

Lin，Yi Qi,et al."Fast QLB algorithm and hypothesis tests in logistic model for ophthalmologic bilateral correlated data".Journal of Biopharmaceutical Statistics (2020).