cor_bin

Performs maximum likelihood estimation (MLE) of the joint distribution
of two binary variables using only marginal summary data from multiple studies.

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>.

Longwen Shang

ebdm

Estimating Bivariate Dependency from Marginal Data

Min Tsao

Xuekui Zhang

cor_bin function

<dl><dt>ni</dt>
<dd>Numeric vector. Sample sizes for each dataset.</dd>
<dt>xi</dt>
<dd>Numeric vector. Count of observations where variable 1 equals 1.</dd>
<dt>yi</dt>
<dd>Numeric vector. Count of observations where variable 2 equals 1.</dd>
<dt>ci_method</dt>
<dd>Character string. Method for confidence interval computation.
Options are <code>"none"</code> (default), <code>"normal"</code>, or <code>"lr"</code> (likelihood ratio).</dd></dl>

Arguments

Estimate the Joint Distribution of Two Binary Variables from Marginal Summaries — cor_bin

<dl>

<dt>ni</dt>
<dd>Numeric vector. Sample sizes for each dataset.</dd>


<dt>xi</dt>
<dd>Numeric vector. Count of observations where variable 1 equals 1.</dd>


<dt>yi</dt>
<dd>Numeric vector. Count of observations where variable 2 equals 1.</dd>


<dt>ci_method</dt>
<dd>Character string. Method for confidence interval computation.
Options are <code>"none"</code> (default), <code>"normal"</code>, or <code>"lr"</code> (likelihood ratio).</dd>

</dl>

cor_bin: Estimate the Joint Distribution of Two Binary Variables from Marginal Summaries

Description

Usage

Value

Arguments

Examples