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CausalFX (version 1.0.1)

Methods for Estimating Causal Effects from Observational Data

Description

Estimate causal effects of one variable on another, currently for binary data only. Methods include instrumental variable bounds, adjustment by a given covariate set, adjustment by an induced covariate set using a variation of the PC algorithm, and an effect bounding method (the Witness Protection Program) based on covariate adjustment with observable independence constraints.

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Version

Install

install.packages('CausalFX')

Monthly Downloads

4

Version

1.0.1

License

GPL (>= 2)

Issues

1

Pull Requests

0

Stars

13

Forks

4

Maintainer

Ricardo Silva

Last Published

May 20th, 2015

Functions in CausalFX (1.0.1)

print.summary.iv

Print Summaries of Binary Instrumental Variable Analyses
summary.iv

Summarize Binary Instrumental Variable Analyses
print.cfx

Prints a CausalFX Problem Instance
wpp

The Witness Protection Program for Causal Effect Estimation
covsearch

Search for Causal Effect Covariate Adjustment
simulateWitnessModel

Generates Synthetic CausalFX Problems
summary.wpp

Summarize Witness Protection Program Outputs
print.summary.covsearch

Print Summaries of Covariate Search Outputs
cfx

Creates a CausalFX Problem Instance
bindagCausalEffectBackdoor

Estimates Average Causal Effects by Covariate Adjustment in Binary Models
iv

Bayesian Analysis of Binary Instrumental Variables
synthetizeCausalEffect

Computes Average Causal Effects by Covariate Adjustment in Binary Models using a Given Causal Model
summary.covsearch

Summarize Covariate Search Outputs
print.summary.wpp

Print Summaries of Witness Protection Program Outputs