Regression models of Pearson correlation coefficient

被引：19
|
作者：
Dufera, Abdisa G. [1 ]
Liu, Tiantian [1 ,2 ]
Xu, Jin [1 ,3 ,4 ,5 ]
机构：
[1] East China Normal Univ, Sch Stat, Shanghai, Peoples R China
[2] Technion Israel Inst Technol, Fac Ind Engn & Management, Haifa, Israel
[3] East China Normal Univ, Key Lab Adv Theory & Applicat Stat & Data Sci, MOE, Shanghai, Peoples R China
[4] East China Normal Univ, Sch Stat, Shanghai 200062, Peoples R China
[5] East China Normal Univ, Key Lab Adv Theory & Applicat Stat & Data Sci, MOE, Shanghai 200062, Peoples R China
来源：
STATISTICAL THEORY AND RELATED FIELDS | 2023年 / 7卷 / 02期
关键词：
Binary responses; bivariate normal responses; Pearson correlation coefficient; regression; EQUALITY;
D O I：
10.1080/24754269.2023.2164970
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We propose two simple regression models of Pearson correlation coefficient of two normal responses or binary responses to assess the effect of covariates of interest. Likelihood-based inference is established to estimate the regression coefficients, upon which bootstrap-based method is used to test the significance of covariates of interest. Simulation studies show the effectiveness of the method in terms of type-I error control, power performance in moderate sample size and robustness with respect to model mis-specification. We illustrate the application of the proposed method to some real data concerning health measurements.
引用
收藏
页码：97 / 106
页数：10
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