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WMAP (version 1.2.0)

Weighted Meta-Analysis with Pseudo-Populations

Description

Implementation of integrative weighting approaches for multiple observational studies and causal inferences. The package features three weighting approaches, each representing a special case of the unified weighting framework, introduced by Guha and Li (2024) , which includes an extension of inverse probability weights for data integration settings.

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Version

Install

install.packages('WMAP')

Monthly Downloads

119

Version

1.2.0

License

GPL-3

Maintainer

Subharup Guha

Last Published

June 17th, 2025

Functions in WMAP (1.2.0)

causal.estimate

Estimate causal effects using FLEXOR or other methods
plot.causal_estimates

Plot method for objects of class 'causal_estimates'
summary.causal_estimates

Summary method for objects of class 'causal_estimates'
demo

Demo Dataset
balancing.weights

Compute balancing weights using FLEXOR or other methods
summary.balancing_weights

Summary method for objects of class 'balancing_weights'