Estimating Bivariate Dependency from Marginal Data
Provides statistical methods for estimating bivariate dependency (correlation) from marginal summary statistics across multiple studies. The package supports three modules: (1) bivariate correlation estimation for binary outcomes, (2) bivariate correlation estimation for continuous outcomes, and (3) estimation of component-wise means and variances under a conditional two-component Gaussian mixture model for a continuous variable stratified by a binary class label. These methods enable privacy-preserving joint estimation when individual-level data are unavailable. The approaches are detailed in Shang, Tsao, and Zhang (2025a) <doi:10.48550/arXiv.2505.03995> and Shang, Tsao, and Zhang (2025b) <doi:10.48550/arXiv.2508.02057>.