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WMAP (version 1.1.0)

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

1.1.0

License

GPL-3

Maintainer

Subharup Guha

Last Published

November 30th, 2024

Functions in WMAP (1.1.0)

plot.causal_estimates

Boxplot of percent ESS
balancing.weights

Compute balancing weights using FLEXOR or other methods
percentESS

Extract percentage sample ESS
mean_diff

Extract causal estimates (mean differences)
sigma_ratio

Extract sigma ratios
causal.estimate

Estimate causal effects using FLEXOR or other methods
print.balancing_weights

Print method for objects of class 'balancing_weights'
get_weights

Extract sample weights
demo

Demo Dataset
print.causal_estimates

Print method for objects of class 'causal_estimates'
summary.balancing_weights

Summary method for objects of class 'balancing_weights'
summary.causal_estimates

Summary method for objects of class 'causal_estimates'