Estimating Bivariate Dependency from Marginal Data
Description
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) and Shang, Tsao, and Zhang (2025b) .