Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 97-106 |
| Number of pages | 10 |
| Journal | Statistical Theory and Related Fields |
| Volume | 7 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2023 |
Keywords
- Binary responses
- Pearson correlation coefficient
- bivariate normal responses
- regression