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

页码：97 / 106

页数：10

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